检索结果-内蒙古大学图书馆

arXiv 2019年

作者： Kang, John Thompson, Reid Aneja, Sanjay Lehman, Constance Trister, Andrew Zou, James Obcemea, Ceferino El Naqa, Issam Dept. of Radiation Oncology University of Rochester Medical Center NY United States Dept. of Radiation Medicine Oregon Health & Science University PortlandOR United States Portland Healthcare System VA United States Dept of Therapeutic Radiology Yale University New HavenNY United States Dept. of Radiology Harvard Medical School Mass General Hospital BostonMA United States Bill & Melinda Gates Foundation SeattleWA United States Dept. of Biomedical Data Science Stanford University. Chan-Zuckerberg Biohub San FranciscoCA Radiation Research Program National Cancer Institute BethesdaMD Singapore Dept. of Radiation Oncology University of Michigan Ann ArborMI United States

Artificial intelligence (AI) is about to touch every aspect of radiotherapy from consultation, treatment planning, quality assurance, therapy delivery, to outcomes reporting. There is an urgent need to train radiation oncologists and medical physicists in data science to help shepherd artificial intelligence solutions into clinical practice. Poorly-trained personnel may do more harm than good when attempting to apply rapidly-developing and complex technologies. As the amount of AI research expands in our field, the radiation oncology community needs to discuss how to educate future generations in this area. In this perspective article by the Training and Education Working Group from the National cancer Institute (NCI) Workshop on AI in Radiation Oncology (Shady Grove, MD, April 4-5, 2019), we provide and discuss Action Points relevant for future trainees interested in radiation oncology artificial intelligence: (1) creating AI awareness and proper conduct;(2) developing a dedicated didactic curriculum;(3) creating a publicly available database of training resources;and (4) accelerating the translation process of AI into clinical practice. Copyright © 2019, The Authors. All rights reserved.

关键词： Radiotherapy

来源：评论

学校读者我要写书评

暂无评论

Author Correction: High p16 expression and heterozygous RB1 loss are biomarkers for CDK4/6 inhibitor resistance in ER+ breast cancer

引用

Nature communications 2022年第1期13卷 6928页

作者： Marta Palafox Laia Monserrat Meritxell Bellet Guillermo Villacampa Abel Gonzalez-Perez Mafalda Oliveira Fara Brasó-Maristany Nusaibah Ibrahimi Srinivasaraghavan Kannan Leonardo Mina Maria Teresa Herrera-Abreu Andreu Òdena Mònica Sánchez-Guixé Marta Capelán Analía Azaro Alejandra Bruna Olga Rodríguez Marta Guzmán Judit Grueso Cristina Viaplana Javier Hernández Faye Su Kui Lin Robert B Clarke Carlos Caldas Joaquín Arribas Stefan Michiels Alicia García-Sanz Nicholas C Turner Aleix Prat Paolo Nuciforo Rodrigo Dienstmann Chandra S Verma Nuria Lopez-Bigas Maurizio Scaltriti Monica Arnedos Cristina Saura Violeta Serra Experimental Therapeutics Group Vall d'Hebron Institute of Oncology Barcelona Spain. Breast Cancer and Melanoma Group Vall d'Hebron Institute of Oncology Barcelona Spain. Department of Medical Oncology Hospital Vall d'Hebron Barcelona Spain. Oncology Data Science Group Vall d'Hebron Institute of Oncology Barcelona Spain. Institute for Research in Biomedicine (IRB Barcelona) Barcelona Spain. Research Program on Biomedical Informatics Universitat Pompeu Fabra Barcelona Spain. Translational Genomics and Targeted Therapies in Solid Tumors August Pi i Sunyer Biomedical Research Institute (IDIBAPS) Barcelona Spain. Service de Biostatistique et d'Epidémiologie Gustave Roussy Villejuif France. Oncostat U1018 Inserm University Paris-Saclay Villejuif France. Bioinformatics Institute (A*STAR) Singapore Singapore. Medica Scientia Innovation Research (MedSIR) Barcelona Spain. The Breast Cancer Now Research Centre London UK. Preclinical Modelling of Pediatric Cancer Evolution Group The Institute of Cancer Research London UK. Translational Molecular Pathology Vall d'Hebron Institute of Research (VHIR) Barcelona Spain. Novartis Pharmaceuticals East Hanover NJ USA. Genentech Inc. South San Francisco California USA. Breast Biology Group Manchester Breast Centre Manchester UK. Cancer Research UK Cambridge UK. CIBERONC Vall d'Hebron Institute of Oncology Barcelona Spain. Growth Factors Laboratory Vall d'Hebron Institute of Oncology Barcelona Spain. Department of Biochemistry and Molecular Biology Universitat Autònoma de Barcelona Barcelona Spain. IMIM (Hospital del Mar Medical Research Institute) Barcelona Spain. Institució Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain. University of Barcelona Barcelona Spain. Department of Medical Oncology Hospital Clinic Barcelona Spain. SOLTI Breast Cancer Research Group Barcelona Spain. Department of Oncology IOB Institute of Oncology Barcelona Spain. Molecular Oncology Group Vall d'Hebron Institute of On

来源：评论

学校读者我要写书评

暂无评论

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

arXiv

引用

arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health

arXiv

引用

arXiv 2021年

作者： Scott, Ryan T. Antonsen, Erik L. Sanders, Lauren M. Hastings, Jaden J.A. Park, Seung-Min Mackintosh, Graham Reynolds, Robert J. Hoarfrost, Adrienne L. Sawyer, Aenor Greene, Casey S. Glicksberg, Benjamin S. Theriot, Corey A. Berrios, Daniel C. Miller, Jack Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Chalk, Stuart Delgado-Aparicio, Guillermo M. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Kalantari, John Khezeli, Kia Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Martin, Hector Garcia Mason, Christopher E. Matar, Mona Mias, George I. Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Parsons-Wingerter, Patricia Prabhu, R.K. Qutub, Amina Ann Rask, Jon Saravia-Butler, Amanda Saria, Suchi Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Yang, Jason H. Zitnik, Marinka Costes, Sylvain V. KBR Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Department of Urology Department of Radiology Stanford University School of Medicine StanfordCA94305 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett FieldCA94035 United States Mortality Research & Consulting Inc. HoustonTX77058 United States Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States UC Space Health Department of Orthopaedic Surgery University of California San Francisco San FranciscoCA94143 United States Center for Health AI Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine Anschutz Medical Campus AuroraCO80045 United States Hasso Plattner Institute for Digital Health at Mount Sinai Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New YorkNY10065 United States Department of Preventive Medicine and Community Health UTMB GalvestonTX77551 United States Human Health and Performance Directorate NASA Johnson Space Center HoustonTX77058 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Data Scienc

Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth-independence, rather than Earth-reliance. Promising developments in the fields of artificial intelligence and machine learning for biology and health can address these needs. We propose an appropriately autonomous and intelligent Precision Space Health system that will monitor, aggregate, and assess biomedical statuses;analyze and predict personalized adverse health outcomes;adapt and respond to newly accumulated data;and provide preventive, actionable, and timely insights to individual deep space crew members and iterative decision support to their crew medical officer. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration, on future applications of artificial intelligence in space biology and health. In the next decade, biomonitoring technology, biomarker science, spacecraft hardware, intelligent software, and streamlined data management must mature and be woven together into a Precision Space Health system to enable humanity to thrive in deep space. © 2021, CC BY.

关键词： Earth (planet)

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to 'Molecular characterisation of hepatocellular carcinoma in patients with non-alcoholic steatohepatitis' [J Hepatol 75 (2021) 865-878]

引用

Journal of hepatology 2021年第6期75卷 1515页

作者： Roser Pinyol Sara Torrecilla Huan Wang Carla Montironi Marta Piqué-Gili Miguel Torres-Martin Leow Wei-Qiang Catherine E Willoughby Pierluigi Ramadori Carmen Andreu-Oller Patricia Taik Youngmin A Lee Agrin Moeini Judit Peix Suzanne Faure-Dupuy Tobias Riedl Svenja Schuehle Claudia P Oliveira Venancio A Alves Paolo Boffetta Anja Lachenmayer Stephanie Roessler Beatriz Minguez Peter Schirmacher Jean-François Dufour Swan N Thung Helen L Reeves Flair J Carrilho Charissa Chang Andrew V Uzilov Mathias Heikenwalder Arun Sanyal Scott L Friedman Daniela Sia Josep M Llovet Liver Cancer Translational Research Laboratory Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Hospital Clínic Universitat de Barcelona Barcelona Catalonia Spain. Sema4 Stamford Connecticut USA. Liver Cancer Translational Research Laboratory Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Hospital Clínic Universitat de Barcelona Barcelona Catalonia Spain Mount Sinai Liver Cancer Program (Divisions of Liver Diseases Department of Hematology/Oncology Department of Medicine Department of Pathology) Tisch Cancer Institute Icahn School of Medicine at Mount Sinai New York USA. Mount Sinai Liver Cancer Program (Divisions of Liver Diseases Department of Hematology/Oncology Department of Medicine Department of Pathology) Tisch Cancer Institute Icahn School of Medicine at Mount Sinai New York USA Department of Anatomical Pathology Singapore General Hospital Singapore Singapore. Division of Chronic Inflammation and Cancer German Cancer Research Center Heidelberg (DKFZ) Heidelberg Germany. Department of Surgical Sciences Vanderbilt University Medical Center Nashville Tennessee USA. Departments of Gastroenterology and Pathology University of São Paulo - School of Medicine São Paulo Brazil. Department of Medical and Surgical Sciences University of Bologna Italy. Department of Visceral Surgery and Medicine Bern University Hospital University of Bern CH-3010 Bern Switzerland. Institute of Pathology University Hospital Heidelberg Germany. Liver Unit Vall d´Hebron Hospital Universitari Liver Diseases Research Group Vall d´Hebron Institut of Research (VHIR) Vall d´Hebron Hospital Campus. CIBERehd Universitat Autonoma de Barcelona Barcelona Catalonia Spain. Newcastle University Translational and Clinical Research Institute and Newcastle University Centre for Cancer Medical School Framlington Place Newcastle Upon Tyne NE2 4HH UK Hepatopancreatobiliary Multidisciplinary Team Newcastle upon Tyne NHS Foundation Trust Freeman Hospital

来源：评论

学校读者我要写书评

暂无评论

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

引用

Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

arXiv

引用

arXiv 2023年

作者： Moawad, Ahmed W. Janas, Anastasia Baid, Ujjwal Ramakrishnan, Divya Saluja, Rachit Ashraf, Nader Jekel, Leon Amiruddin, Raisa Adewole, Maruf Albrecht, Jake Anazodo, Udunna Aneja, Sanjay Anwar, Syed Muhammad Bergquist, Timothy Calabrese, Evan Chiang, Veronica Chung, Verena Conte, Gian Marco Marco Dako, Farouk Eddy, James Ezhov, Ivan Familiar, Ariana Farahani, Keyvan Iglesias, Juan Eugenio Jiang, Zhifan Johanson, Elaine Kazerooni, Anahita Fathi Kofler, Florian Krantchev, Kiril LaBella, Dominic Van Leemput, Koen Li, Hongwei Bran Linguraru, Marius George Link, Katherine E. Liu, Xinyang Maleki, Nazanin Meier, Zeke Menze, Bjoern H. Moy, Harrison Osenberg, Klara Piraud, Marie Reitman, Zachary Shinohara, Russel Takeshi Tahon, Nourel hoda Nada, Ayman Velichko, Yuri S. Wang, Chunhao Wiestler, Benedikt Wiggins, Walter Shafique, Umber Willms, Klara Avesta, Arman Bousabarah, Khaled Chakrabarty, Satrajit Gennaro, Nicolo Holler, Wolfgang Kaur, Manpreet LaMontagne, Pamela Lin, MingDe Lost, Jan Marcus, Daniel S. Maresca, Ryan Merkaj, Sarah Nada, Ayaman Pedersen, Gabriel Cassinelli von Reppert, Marc Sotiras, Aristeidis Teytelboym, Oleg Tillmans, Niklas Westerhoff, Malte Youssef, Ayda Godfrey, Devon Floyd, Scott Rauschecker, Andreas Villanueva-Meyer, Javier Pflüger, Irada Cho, Jaeyoung Bendszus, Martin Brugnara, Gianluca Cramer, Justin Perez-Carillo, Gloria Guzman J. Johnson, Derek R. Kam, Anthony Kwan, Benjamin Yin Ming Lai, Lillian Lall, Neil U. Memon, Fatima Patro, Satya Narayana Petrovic, Bojan So, Tiffany Y. Thompson, Gerard Wu, Lei Schrickel, E. Brooke Bansal, Anu Barkhof, Frederik Besada, Cristina Chu, Sammy Druzgal, Jason Dusoi, Alexandru Farage, Luciano Feltrin, Fabricio Fong, Amy Fung, Steve H. Gray, R. Ian Ikuta, Ichiro Iv, Michael Postma, Alida A. Mahajan, Amit Joyner, David Krumpelman, Chase Letourneau-Guillon, Laurent Lincoln, Christie M. Maros, Mate E. Miller, Elka Morón, Fanny Nimchinsky, Esther A. Ozsarlak, Ozkan Patel, Uresh Rohatgi, Saurabh Saha, Atin Sayah, Anousheh Schwartz, Eric D. Shih, Robert Shiroishi, Mark Trinity health Mid Atlantic Hosiptals DarbyPA United States Department of Radiology and Biomedical Imaging Yale School of Medicine New HavenCT United States Division of Computational Pathology Department of Pathology and Laboratory Medicine School of Medicine Indiana University IndianapolisIN United States Department of Electical and Computer Engineering Cornell University Cornell Tech New YorkNY United States Department of Radiology Weill Cornell Medicine New YorkNY United States ImagineQuant Children’s Hospital of Philadelphia PhiladelphiaPA United States College of Medicine Alfaisal University Riyadh Saudi Arabia DKFZ Division of Translational Neurooncology The WTZ German Cancer Consortium DKTK Partner Site University Hospital Essen Essen Germany Medical Artificial Intelligence Lab Crestview Radiology Lagos Nigeria Sage Bionetworks SeattleWA United States Montreal Neurological Institute McGill University Montreal Canada lab Crestview Radiology Lagos Nigeria Department of Therapeutic Radiology Yale School of Medicine New HavenCT United States Sheikh Zayed Institute for Pediatric Surgical Innovation Children’s National Hospital WashingtonDC United States Department of Radiology Mayo Clinic RochesterMN United States Department of Radiology Duke University Medical Center DurhamNC United States Department of Neurosurgery Yale School of Medicine New HavenCT United States Center for Global Health Perelman School of Medicine University of Pennsylvania PA United States Department of Informatics Technical University Munich Germany Children’s Hospital of Philadelphia University of Pennsylvania PhiladelphiaPA United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD United States Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Children’s National Hospital WashingtonDC United States PrecisionFDA U.S. Food and Drug Administration S

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well-annotated, diverse d

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance

引用

Nature genetics 2024年第10期56卷 2281页

作者： Qingbo S Wang Takanori Hasegawa Ho Namkoong Ryunosuke Saiki Ryuya Edahiro Kyuto Sonehara Hiromu Tanaka Shuhei Azekawa Shotaro Chubachi Yugo Takahashi Saori Sakaue Shinichi Namba Kenichi Yamamoto Yuichi Shiraishi Kenichi Chiba Hiroko Tanaka Hideki Makishima Yasuhito Nannya Zicong Zhang Rika Tsujikawa Ryuji Koike Tomomi Takano Makoto Ishii Akinori Kimura Fumitaka Inoue Takanori Kanai Koichi Fukunaga Seishi Ogawa Seiya Imoto Satoru Miyano Yukinori Okada Department of Genome Informatics Graduate School of Medicine University of Tokyo Tokyo Japan. qingbow@m.u-tokyo.ac.jp. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. qingbow@m.u-tokyo.ac.jp. M&D Data Science Center Tokyo Medical and Dental University Tokyo Japan. Department of Infectious Diseases Keio University School of Medicine Tokyo Japan. hounamugun@keio.jp. Department of Pathology and Tumor Biology Kyoto University Kyoto Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Department of Respiratory Medicine and Clinical Immunology Osaka University Graduate School of Medicine Suita Japan. Department of Genome Informatics Graduate School of Medicine University of Tokyo Tokyo Japan. Division of Pulmonary Medicine Department of Medicine Keio University School of Medicine Tokyo Japan. Faculty of Medicine Osaka University Suita Japan. Center for Data Sciences Brigham and Women's Hospital Harvard Medical School Boston MA USA. Divisions of Genetics and Rheumatology Department of Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA. Laboratory of Children's Health and Genetics Division of Health Science Osaka University Graduate School of Medicine Suita Japan. Department of Pediatrics Osaka University Graduate School of Medicine Suita Japan. Division of Genome Analysis Platform Development National Cancer Center Research Institute Tokyo Japan. Institute for the Advanced Study of Human Biology (WPI-ASHBi) Kyoto University Kyoto Japan. Health Science Research and Development Center (HeRD) Tokyo Medical and Dental University Tokyo Japan. Laboratory of Veterinary Infectious Disease Department of Veterinary Medicine Kitasato University Tokyo Japan. Department of Respiratory Medicine Nagoya University Graduate School of Medicine Nagoya Japan. In

来源：评论

学校读者我要写书评

暂无评论

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

引用

The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

关键词：

来源：评论

学校读者我要写书评

暂无评论

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci (vol 50, pg 928, 2018)

引用

NATURE GENETICS 2019年第2期51卷 363-363页

作者： Schumacher, Fredrick R. Al Olama, Ali Amin Berndt, Sonja I. Benlloch, Sara Ahmed, Mahbubl Saunders, Edward J. Dadaev, Tokhir Leongamornlert, Daniel Anokian, Ezequiel Cieza-Borrella, Clara Goh, Chee Brook, Mark N. Sheng, Xin Fachal, Laura Dennis, Joe Tyrer, Jonathan Muir, Kenneth Lophatananon, Artitaya Stevens, Victoria L. Gapstur, Susan M. Carter, Brian D. Tangen, Catherine M. Goodman, Phyllis J. Thompson, Ian M., Jr. Batra, Jyotsna Chambers, Suzanne Moya, Leire Clements, Judith Horvath, Lisa Tilley, Wayne Risbridger, Gail P. Gronberg, Henrik Aly, Markus Nordstrom, Tobias Pharoah, Paul Pashayan, Nora Schleutker, Johanna Tammela, Teuvo L. J. Sipeky, Csilla Auvinen, Anssi Albanes, Demetrius Weinstein, Stephanie Wolk, Alicja Hakansson, Niclas West, Catharine M. L. Dunning, Alison M. Burnet, Neil Mucci, Lorelei A. Giovannucci, Edward Andriole, Gerald L. Cussenot, Olivier Cancel-Tassin, Geraldine Koutros, Stella Freeman, Laura E. Beane Sorensen, Karina Dalsgaard Orntoft, Torben Falck Borre, Michael Maehle, Lovise Grindedal, Eli Marie Neal, David E. Donovan, Jenny L. Hamdy, Freddie C. Martin, Richard M. Travis, Ruth C. Key, Tim J. Hamilton, Robert J. Fleshner, Neil E. Finelli, Antonio Ingles, Sue Ann Stern, Mariana C. Rosenstein, Barry S. Kerns, Sarah L. Ostrer, Harry Lu, Yong-Jie Zhang, Hong-Wei Feng, Ninghan Mao, Xueying Guo, Xin Wang, Guomin Sun, Zan Giles, Graham G. Southey, Melissa C. MacInnis, Robert J. FitzGerald, Liesel M. Kibel, Adam S. Drake, Bettina F. Vega, Ana Gomez-Caamano, Antonio Szulkin, Robert Eklund, Martin Kogevinas, Manolis Llorca, Javier Castano-Vinyals, Gemma Penney, Kathryn L. Stampfer, Meir Park, Jong Y. Sellers, Thomas A. Lin, Hui-Yi Stanford, Janet L. Cybulski, Cezary Wokolorczyk, Dominika Lubinski, Jan Ostrander, Elaine A. Geybels, Milan S. Nordestgaard, Borge G. Nielsen, Sune F. Weischer, Maren Bisbjerg, Rasmus Roder, Martin Andreas Iversen, Peter Brenner, Hermann Cuk, Katarina Holleczek, Bernd Maier, Christiane Luedeke, Manuel Schnoeller, Thomas Kim, Jeri Logothetis, Christopher J. John, E Department of Population and Quantitative Health Sciences Case Western Reserve University Cleveland USA Seidman Cancer Center University Hospitals Cleveland USA Royal Marsden NHS Foundation Trust London UK Department of Public Health and Primary Care Centre for Cancer Genetic Epidemiology University of Cambridge Strangeways Research Laboratory Cambridge UK Department of Clinical Neurosciences University of Cambridge Cambridge UK Division of Cancer Epidemiology and Genetics National Cancer Institute NIH Bethesda USA Institute of Cancer Research London UK Department of Preventive Medicine Keck School of Medicine University of Southern California/Norris Comprehensive Cancer Center Los Angeles USA Fundación Pública Galega de Medicina Xenómica–SERGAS Grupo de Medicina Xenómica CIBERER IDIS Santiago de Compostela Spain Department of Oncology Centre for Cancer Genetic Epidemiology Strangeways Laboratory University of Cambridge Cambridge UK Division of Population Health Health Services Research and Primary Care University of Manchester Manchester UK Warwick Medical School University of Warwick Coventry UK Epidemiology Research Program American Cancer Society Atlanta USA SWOG Statistical Center Fred Hutchinson Cancer Research Center Seattle USA CHRISTUS Santa Rosa Hospital–Medical Center San Antonio USA Institute of Health and Biomedical Innovation and School of Biomedical Sciences Queensland University of Technology Brisbane Australia Australian Prostate Cancer Research Centre–Qld Translational Research Institute Brisbane Australia Menzies Health Institute of Queensland Griffith University Nathan Australia Cancer Council Queensland Fortitude Valley Australia Chris O’Brien Lifehouse (COBLH) Camperdown Australia Garvan Institute of Medical Research Sydney Australia Dame Roma Mitchell Cancer Research Centre University of Adelaide Adelaide Australia Monash Biomedicine Discovery Institute Cancer Program Prostate Cancer Research Program Department of Anatom

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：