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P1.27-04 Phase II Basket Trial of Dual Anti-CTLA-4 and Anti-PD-1 Blockade in Rare Tumors (DART) SWOG S1609: Bronchioloalveolar Carcinoma of the Lung

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Journal of Thoracic Oncology 2023年第11期18卷 S284-S285页

作者： Y.K. Chae M. Othus S.P. Patel D.E. Gerber T. Tanvetyanon L.I.-Y. Chung H.S. Kim C.M. McLeod H.X. Chen E. Sharon H. Streicher C.W. Ryan C.D. Blanke R. Kurzrock Northwestern University CHICAGO/IL/USA SWOG Statistics and Data Management Center Seattle/WA/USA University of California at San Diego Moores Cancer Center La Jolla/CA/USA University of Texas Southwestern Medical Center Simmons Cancer Center Dallas/TX/USA Moffitt Cancer Center Tampa/FL/USA SWOG Data Operations Center Seattle/WA/USA National Cancer Institute Investigational Drug Branch Cancer Therapy Evaluation Program Bethesda/MD/USA Oregon Health & Science University Portland/OR/USA SWOG Group Chair’s Office Knight Cancer Institute Portland/OR/USA Medical College of Wisconsin Milwaukee/WI/USA

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Health Assistant Wearable-Based data science System Model: A Pilot Study 3

Health Assistant Wearable-Based Data Science System Model: A...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Budiarto, Arif Febriana, Trisna Suparyanto, Teddy Caraka, Rezzy Eko Pardamean, Bens Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Indonesia Faculty of Science National University of Malaysia School of Mathematical Science Bangi43000 Malaysia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The rapid development of Information and Communication Technology (ICT) has an impact on the innovation of new technology that gives benefits for health. One of its latest development is wearable device technology. Nowadays, the growth of this technology market is very positive. But unfortunately the growth of this technology is not followed by the availability of supporting applications that provide maximum benefits for users by utilizing personal health and activity data. This paper is intended to provide a report of our initial research in developing a health assistant solution that utilizes wearable device generated data. The whole research process is executed using Design Thinking approach that put the users as the main consideration. This initial research is started by designing a field research that can potentially gathered users' data generated from wearable device. A series of statistical and machine learning techniques are presented to analyze time series data to create a model. Finally, to implement the model, a mobile application prototype is also proposed. The outcomes from this initial research will be used to develop a fully working solution. © 2018 IEEE.

关键词： Learning systems

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Estimating international trade status of countries from global liner shipping networks

arXiv

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arXiv 2020年

作者： Xu, Mengqiao Pan, Qian Xia, Haoxiang Masuda, Naoki School of Economics and Management Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian City Liaoning Province116024 China Department of Mathematics University at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Maritime shipping is a backbone of international trade and thus the world economy. Vessels travel from a port of one country to another on networks of ports to carry cargos, which contribute to countries’ international trade values. We hypothesize that ports that involve transshipment activities serve as a third-party middleman to mediate trade between two foreign countries and contribute to the corresponding country's status in international trade. We test this hypothesis using a port-level data set of global liner shipping services. We propose two indices that quantify the importance of countries in the global liner shipping network and show that they explain a large amount of variation in the international trade value and related measures of individual countries. These results support a long-standing view in maritime economics, which has yet been directly tested, that countries that are strongly integrated into the global maritime transportation network have enhanced access to global markets and trade opportunities. Copyright © 2020, The Authors. All rights reserved.

关键词： International trade

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data-driven modeling reveals a universal dynamic underlying the COVID-19 pandemic under social distancing

arXiv

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arXiv 2020年

作者： Marsland, Robert Mehta, Pankaj Department of Physics Boston University BostonMA02215 United States Biological Design Center Boston University BostonMA02215 United States Microbiome Initiative Boston University BostonMA02215 United States Bioinformatics Program Boston University BostonMA02215 United States College of Data Science Boston University BostonMA02215 United States

We show that the COVID-19 pandemic under social distancing exhibits universal dynamics. The cumulative numbers of both infections and deaths quickly cross over from exponential growth at early times to a longer period of power law growth, before eventually slowing. In agreement with a recent statistical forecasting model by the IHME, we show that this dynamics is well described by the erf function. Using this functional form, we perform a data collapse across countries and US states with very different population characteristics and social distancing policies, confirming the universal behavior of the COVID-19 outbreak. We show that the predictive power of statistical models is limited until a few days before curves flatten, forecast deaths and infections assuming current policies continue and compare our predictions to the IHME models. We present simulations showing this universal dynamics is consistent with disease transmission on scale-free networks and random networks with non-Markovian transmission dynamics. Copyright © 2020, The Authors. All rights reserved.

关键词： Dynamics

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Brightness asymmetry of black hole images as a probe of observer inclination

arXiv

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arXiv 2021年

作者： Medeiros, Lia Chan, Chi-Kwan Narayan, Ramesh Özel, Feryal Psaltis, Dimitrios School of Natural Sciences Institute for Advanced Study 1 Einstein Drive PrincetonNJ08540 United States Steward Observatory and Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States

The Event Horizon Telescope recently captured images of the supermassive black hole in the center of the M87 galaxy, which show a ring-like emission structure with the South side only slightly brighter than the North side. This relatively weak asymmetry in the brightness profile along the ring has been interpreted as a consequence of the low inclination of the observer (around 17◦ for M87), which suppresses the Doppler beaming and boosting effects that might otherwise be expected due to the nearly relativistic velocities of the orbiting plasma. In this work, we use a large suite of general relativistic magnetohydrodynamic simulations to reassess the validity of this argument. By constructing explicit counter examples, we show that low-inclination is a sufficient but not necessary condition for images to have low brightness asymmetry. Accretion flow models with high accumulated magnetic flux close to the black hole horizon (the so-called magnetically arrested disks) and low black-hole spins have angular velocities that are substantially smaller than the orbital velocities of test particles at the same location. As a result, such models can produce images with low brightness asymmetry even when viewed edge on. Copyright © 2021, The Authors. All rights reserved.

关键词： Luminance

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Markerless tracking enables distinction between strategic compensation and functional recovery after spinal cord injury

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Experimental Neurology 2022年 354卷 114085页

作者： Mah, Kar Men Badillo-Martinez, Abdiel Jann, Victor Bixby, John L. Lemmon, Vance P. Miami Project to Cure Paralysis University of Miami Miller School of Medicine Miami 33136 FL United States Dept. of Neurological Surgery University of Miami Miller School of Medicine Miami 33136 FL United States Institute for Data Science and Computing University of Miami Miller School of Medicine Miami 33136 FL United States Dept. of Molecular and Cellular Pharmacology University of Miami Miller School of Medicine Miami 33136 FL United States Sylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami 33136 FL United States Neuroscience Graduate Program University of Miami Miller School of Medicine Miami 33136 FL United States University of California Berkeley United States

Injuries to the cervical spinal cord represent around 60% of all spinal cord injuries (SCIs). A major priority for patients with cervical SCIs is the recovery of any hand or arm function. The similarities between human and rodent “reach-to-eat movements” indicate that analyzing mouse forelimb reaching behavior may be a method of identifying clinically relevant treatments for people with cervical SCIs. One popular behavioral measure of forelimb functional recovery comprises the Single Pellet Retrieval Task (SPRT). The most common outcome measure for this task, however (percentage of pellets successfully retrieved), cannot readily distinguish between recovery of pre-injury motor patterns and strategic compensation. Our objective was to establish outcome measures for the SPRT that are readily adopted by different investigators and capable of measuring recovery of limb function after SCI. We used a simple semi-automated approach to high-speed tracking of mouse forepaw movements during pellet retrieval. DeepLabCut™, a machine learning based computer vision software package, was used to track individual features of the mouse forepaw, allowing a more detailed assessment of reaching behavior after SCI. Interestingly, kinematic analysis of movements pre- and post-injury illuminated persistent deficits in specific features of the reaching motor patterns, namely pronation and paw trajectory, that were poorly correlated with recovery of the ability to successfully retrieve pellets. Thus, we have developed an inexpensive method for detailed analysis of mouse reach-to-eat behavior following SCI. Further, our results suggest that binary success/fail outcome measures primarily assess an animal's ability to compensate rather than a restoration of normal function in the injured pathways and networks. © 2022 Elsevier Inc.

关键词： DeepLabCut Forelimb Machine learning Mouse kinematics Pronation Reaching Spinal cord injury

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Study on Machine Learning Techniques with Conventional Tools for Payment Fraud Detection

Study on Machine Learning Techniques with Conventional Tools...

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International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Harindu Mudunkotuwa Mudunkotuwe Hitiwadi Vidanelage Treepatchara Tasnavijitvong Panit Suwimonsatein Phayung Meesad Information and Data Science Program King Mongkut’s University of Technology North Bangkok Bangkok Thailand Faculty of Information Technology King Mongkut’s University of Technology North Bangkok Bangkok Thailand

Payment fraud is intentional deception with the purpose of obtaining financial gain or causing loss by implicit or explicit trick, committed by many parties in order to gain significant financial benefits. That had been a major reason for personal financial losses that account over a billion losses a year. At the same time, fraud detection has been improved and currently is embraced by the cutting-edge information technology “Machine Learning”. However, majority of the available studies have been studying with the deep high-end techniques with various costly technologies, and focusing on accuracy and time of the model. They have also been limited to past fraud histories. This study is conducted with multiple machine learning techniques with the use of synthesized dataset, which is not limited to the history, and our study is performed by using the conventional open source data science tools. However, the results seem to be above the expectation.

关键词： Machine learning Prediction algorithms Multilayer perceptrons Tools data science Gaussian distribution

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A Breakup Machine Learning Approach for Breast Cancer Prediction

A Breakup Machine Learning Approach for Breast Cancer Predic...

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International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Sabari Vishnu Jayanthan Jaikrishnan Orawan Chantarakasemchit Phayung Meesad Information and Data Science Program King Mongkut’s University of Technology North Bangkok Bangkok Thailand Faculty of Information Technology King Mongkut’s University of Technology North Bangkok Bangkok Thailand

Breast cancer is one of the most common cancers and is the major cause of cancer-related deaths in women worldwide. Breast cancer is a disease in which cells in the breast grow in a rapid state and out of control. Breast cancer can grow in different parts of the breast and may or may not spread outside the breast. If caught on early stage, the breast cancer can be cured before they spread but if the cancer cells have spread to other parts of the body, usually it is hard to cure. Early diagnosis of breast cancer might help increasing the life-span of cancer affected women. In this paper, a novel method for prediction of breast cancer, that enhances the accuracy using machine learning is proposed using six machine learning algorithms. The unbiased estimates of the algorithms are measured using k-fold cross-validation method. This proposed approach proves to increase the accuracy of traditional machine learning algorithms.

关键词： Breast cancer Machine learning algorithms Classification algorithms Prediction algorithms Machine learning Decision trees

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O63: Leveraging global and local genomic data to guide equitable carrier screening: From Genome Aggregation database (gnomAD) to Qatar Genome

Genetics in Medicine Open

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Genetics in Medicine Open 2025年 3卷 102632-102632页

作者： Aarabi, Mahmoud Mbarek, Hamdi Bashar, Aryan Soman, Vishal Al-Mulla, Hajer Nkrumah, Esther Schmitz, Matthew Darabi, Helia Wang, John Kiehl, Paris Sethi, Rahil Saad, Chadi Rajkovic, Aleksandar Yatsenko, Svetlana Chandran, Uma Departments of Pathology and Obstetrics Gynecology and Reproductive Sciences University of Pittsburgh School of Medicine； Medical Genetics and Genomics Laboratories University of Pittsburgh Medical Center (UPMC) Pittsburgh PA Qatar Genome Program Qatar Foundation； Qatar Precision Health Institute Doha Qatar Data Science Graduate Program University of Colorado Boulder Boulder CO Department of Biomedical Informatics University of Pittsburgh School of Medicine Pittsburgh PA Joan H. Marks Graduate Program in Human Genetics Sarah Lawrence College New York NY Temerty Faculty of Medicine University of Toronto Toronto ON Canada Medical Genetics and Genomics Laboratories University of Pittsburgh Medical Center (UPMC) Department of Pediatrics University of Pittsburgh School of Medicine Pittsburgh PA Department of Microbiology Immunology and Pathology Colorado State University Fort Collins CO Department of Pathology and Institute of Human Genetics University of California San Francisco San Francisco CA Department of Pathology Stanford University School of Medicine Stanford CA

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Author Correction: Communities conditionally support deployment of direct air capture for carbon dioxide removal in the United States

Communications Earth & Environment

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Communications Earth & Environment 2024年第1期5卷 1页

作者： Celina Scott-Buechler Bruce Cain Khalid Osman Nicole M. Ardoin Robert B. Jackson Catherine Fraser Grace Adcox Emily Polk Emmett Interdisciplinary Program in Environment & Resources (E-IPER) Stanford University Stanford CA USA Political Science Stanford University Stanford CA USA Civil and Environmental Engineering Stanford University Stanford CA USA Environmental Behavioral Sciences Stanford University Stanford CA USA Woods Institute for the Environment Stanford University Stanford CA USA Precourt Institute for Energy Stanford University Stanford CA USA McCourt School of Public Policy Georgetown University Washington DC USA Data for Progress Washington DC USA Writing and Rhetoric Studies Stanford University Stanford CA USA

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