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Targeted Next Generation Sequencing Reveals Actionable Variants As Potential Therapeutic Targets In Vulvar Melanoma: A Case Study Analysis

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International Journal of Gynecological Cancer 2025年第2期35卷

作者： Simona Maria Fragomeni Alex Federico Alice Dal Miglio Angelo Minucci Alessia Perrucci Luciano Giaco' Mina Karimi Giulia Bravetti Tina Pasciuto Ernesto Rossi Giovanni Schinzari Ketty Peris Alessando Di Stefani Angela Santoro Valentina Iacobelli Camilla Nero Giovanni Scambia Giorgia Garganese Unità di Ginecologia Oncologica Dipartimento Scienze della Salute della Donna del Bambino e di Sanità Pubblica Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Sezione Ginecologia e Ostetricia Dipartimento Universitario Scienze della Vita e Sanità Pubblica Università Cattolica del Sacro Cuore Rome Italy Genomics Research Core facility Gemelli Science and Technology Park (G-STeP) Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Bioinformatics Research Core Facility Gemelli Science and Technology Park (G-STeP) Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Data Collection Core Facility Gemelli Science and Technology Park (G-STeP) Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Medical Oncology Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Medical Oncology Università Cattolica del Sacro Cuore Rome Italy UOC di Dermatologia Dipartimento di Scienze Mediche e Chirurgiche Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Dipartimento di Medicina e Chirurgia Traslazionale Università Cattolica del Sacro Cuore Rome Italy Unità Operativa Complessa Anatomia Patologica Generale Dipartimento di Scienze Della Salute Della Donna del Bambino e di Sanità Pubblica Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Unità operativa di Chirurgia degli Organi Genitali Esterni Femminili Divisione di Ginecologia Oncologica Dipartimento Scienze della Salute della Donna del Bambino e di Sanità Pubblica Fondazione Policlinico Universitario A. Gemelli IRCCS； Gemelli Women Health Center for Digital and Personalized Medicine Sezione Ginecologia e Ostetricia Dipartimento Universitario Scienze della Vita e Sanità Pubblica Università Cattolica del Sacro Cuore Rome Italy Gemelli Women Health Center for Digital and Personalized Medicine Dipartimento Scienze della Vita e Sanità Pubblica all’Università Cattolica del Sacro Cuore Rome Italy

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We are what we experienced before birth: Lessons from epigenetics

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World Allergy Organization Journal 2020年第8期13卷 100361-100361页

作者： Saskia Trump Loreen Thürmann Matthias Klös Tobias Polte Roland Eils Irina Lehmann Charité - Universitätmedizin Berlin and Berlin Institute of Health Molecular Epidemiology Unit Berlin Germany Department of Environmental Immunology Helmholtz Centre for Environmental Research - UFZ Leipzig Germany Charité - Universitätmedizin Berlin and Berlin Institute of Health Center for Digital Health Berlin Germany Heidelberg University Hospital Health Data Science Unit Heidelberg Germany

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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OTHR-04. DEVELOPMENT OF A FUNCTIONAL PLATFORM FOR REAL-TIME PERSONALIZED DRUG SENSITIVITY PROFILING OF PATIENT-DERIVED 3D FRESH TUMOR TISSUE CULTURES IN THE PEDIATRIC PRECISION ONCOLOGY PROGRAM INFORM

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Neuro-Oncology 2023年第SUPPLEMENT_1期25卷 i74–i75页

作者： Heike Peterziel Nora Jamaladdin Dina ElHarouni Xenia F Gerloff Sonja Herter Petra Fiesel Yannick Berker Mirjam Blattner-Johnson Kathrin Schramm Barbara C Jones David Reuss Laura Turunen Aileen Friedenauer Tim Holland-Letz Martin Sill Lena Weiser Christopher Previti Gnanaprakash Balasubramanian Nicolas U Gerber Johannes Gojo Caroline Hutter Ingrid Øra Olli Lohi Antonis Kattamis Bram de Wilde Frank Westermann Stephan Tippelt Norbert Graf Michaela Nathrath Monika Sparber-Sauer Astrid Sehested Christof M Kramm Uta Dirksen Olli Kallioniemi Stefan M Pfister Cornelis M van Tilburg David T W Jones Jani Saarela Vilja Pietiäinen Natalie Jäger Matthias Schlesner Annette Kopp-Schneider Sina Oppermann Till Milde Olaf Witt Ina Oehme Hopp Children’s Cancer Center Heidelberg (KiTZ) Heidelberg Germany Clinical Cooperation Unit Pediatric Oncology German Cancer Research Center (DKFZ) National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Consortium (DKTK) Heidelberg Germany Bioinformatics and Omics Data Analytics German Cancer Research Center (DKFZ) Division of Pediatric Neurooncology German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Clinical Cooperation Unit Neuropathology German Cancer Research Center (DKFZ) Heidelberg Germany Division of Pediatric Glioma Research German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Division of Pediatric Glioma Research German Cancer Research Center (DKFZ) Department of Pediatric Oncology Hematology Immunology and Pulmonology Heidelberg University Hospital and German Cancer Consortium (DKTK) Heidelberg Germany Department Neuropathology at Institute of Pathology Heidelberg University Hospital Heidelberg Germany Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Heidelberg Germany Division of Pediatric Neurooncology German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Core Facility Omics IT and Data Management (ODCF) German Cancer Research Center (DKFZ) Heidelberg Germany Department of Oncology University Children’s Hospital Zürich Zürich Switzerland Department of Pediatrics and Adolescent Medicine Comprehensive Cancer Center and Comprehensive Center for Pediatrics Medical University of Vienna Vienna Austria St. Anna Children’s Hospital Department of Pediatrics and Adolescent Medicine Medical University of Vienna and St. Anna Children’s Cancer Research Institute (CCRI) Vienna Austria Children’s Hospital Pediatric Oncology Skåne University Hospital Lund &amp Karolinska Univ

The international precision oncology program INFORM enrolls relapsed/refractory pediatric cancer patients for comprehensive molecular analysis. We report a two-year pilot study implementing ex vivo drug sensitivity profiling (DSP) using a library of 75-78 clinically relevant drugs. We included 132 viable tumor samples from 35 pediatric oncology centers in seven countries. DSP was conducted on multicellular fresh tumor tissue spheroid cultures in 384-well plates with an overall mean processing time of three weeks. In 89 cases (67%), sufficient viable tissue was received; 69 (78%) passed internal quality controls. The DSP results matched the identified molecular targets, including BRAF, ALK, MET and TP53 status. Drug vulnerabilities were identified in 80% of cases lacking actionable (very) high-evidence molecular events, adding value to the molecular data. Striking parallels between clinical courses and the DSP results were observed in selected patients. Overall, DSP in clinical real-time is feasible in international multicenter precision oncology programs.

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Author Correction: Cell segmentation-free inference of cell types from in situ transcriptomics data

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Nature communications 2021年第1期12卷 4103页

作者： Jeongbin Park Wonyl Choi Sebastian Tiesmeyer Brian Long Lars E Borm Emma Garren Thuc Nghi Nguyen Bosiljka Tasic Simone Codeluppi Tobias Graf Matthias Schlesner Oliver Stegle Roland Eils Naveed Ishaque Berlin Institute of Health at Charité-Universitätsmedizin Berlin Digital Health Center Kapelle-Ufer 2 10117 Berlin Germany. Faculty of Biosciences Heidelberg University Heidelberg Germany. Division of Computational Genomics and System Genetics German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Computer Science Boston University Boston MA USA. Allen Institute for Brain Science Seattle WA USA. Division of molecular neurobiology Department of medical biochemistry and biophysics Karolinska Institutet Stockholm Sweden. Bioinformatics and Omics Data Analytics German Cancer Research Center (DKFZ) Heidelberg Germany. Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany. Berlin Institute of Health at Charité-Universitätsmedizin Berlin Digital Health Center Kapelle-Ufer 2 10117 Berlin Germany. roland.eils@bih-charite.de. Health Data Science Unit Heidelberg University Hospital Heidelberg Germany. roland.eils@bih-charite.de. Berlin Institute of Health at Charité-Universitätsmedizin Berlin Digital Health Center Kapelle-Ufer 2 10117 Berlin Germany. naveed.ishaque@bih-charite.de.

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China Kidney Disease Network (CK-NET) 2017–2018 Annual data Report

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Kidney International Supplements 2025年第1期14卷 e1-e133页

作者： Zhang, Luxia Zhao, Ming-Hui Zuo, Li Zhang, Hong Wang, Yue Wang, Haibo Yu, Feng Yang, Chao Gao, Bixia Chu, Hong Gan, Lanxia Guo, Qi Hao, Jianguo He, Daijun Hong, Shenda Li, Chenglong Li, Pengfei Long, Jianyan Mao, Huijuan Qin, Yingying Shi, Ying Sun, Xiaoyu Tang, Wen Wang, Fulin Wang, Jinwei Wang, Wanzhou Wei, Shaoqing Wen, Fengyu Yao, Xingchen Yang, Guang Yang, Ling Ye, Jianhua Yuan, Qiongjing Zhang, Dongliang Zhang, Feifei Zhang, Ping Zhang, Zhilong Zhao, Xinju Zhou, Zhiye Renal Division Department of Medicine Peking University First Hospital Peking University Institute of Nephrology Beijing China National Institute of Health Data Science at Peking University Beijing China Advanced Institute of Information Technology Peking University Zhejiang Hangzhou China Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases Chinese Academy of Medical Sciences Beijing China Center for Digital Health and Artificial Intelligence Peking University First Hospital Beijing China State Key Laboratory of Vascular Homeostasis and Remodeling Peking University Beijing China Peking-Tsinghua Center for Life Sciences Beijing China Department of Nephrology Peking University People's Hospital Beijing China Department of Nephrology Peking University Third Hospital Beijing China Research Centre of Big Data and Artificial Intelligence for Medicine First Affiliated Hospital of Sun Yat-Sen University Guangdong Guangzhou China Department of Nephrology Peking University International Hospital Beijing China Renal Division Department of Medicine Peking University First Hospital Peking University Institute of Nephrology Beijing China China Standard Medical Information Research Center Guangdong Shenzhen China Renal Division Department of Medicine Peking University First Hospital Kidney Disease Center The First Affiliated Hospital College of Medicine Zhejiang University Zhejiang Hangzhou China Clinical Trial Unit The First Affiliated Hospital of Sun Yat-sen University Guangdong Guangzhou China Department of Nephrology The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Jiangsu Nanjing China Science at Peking University Beijing China Department of Nephrology General Hospital of Ningxia Medical University Ningxia Yinchuang China Department of Nephrology Xiangya Hospital Central South University Hunan Changsha China Department of Nephrology Beijing Jishuitan Hospital Beijing China

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Corrigendum to "Reduced grip strength potentially indicates depression: Investigating multicontinental databases" [J. Affect. Disord., 323 (2023) 426-434]

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Journal of affective disorders 2023年 326卷 268页

作者： Jae Won Oh Sun Mi Kim Deokjong Lee Dong Keon Yon Seung Won Lee Lee Smith Karel Kostev Ai Koyanagi Marco Solmi Andre F Carvalho Jae Il Shin Nak-Hoon Son San Lee Department of Psychiatry Yongin Severance Hospital Yonsei University College of Medicine Yongin Republic of Korea. Department of Nursing Sorabol University Gyeongju Republic of Korea. Department of Psychiatry Yongin Severance Hospital Yonsei University College of Medicine Yongin Republic of Korea Department of Psychiatry and the Institute of Behavioral Science in Medicine Yonsei University College of Medicine Seoul Republic of Korea. Center for Digital Health Medical Science Research Institute Kyung Hee University Medical Center Kyung Hee University College of Medicine Seoul Republic of Korea. Department of Data Science Sejong University College of Software Convergence Seoul Republic of Korea Sungkyunkwan University School of Medicine Suwon Republic of Korea. Centre for Health Performance and Wellbeing Anglia Ruskin University Cambridge UK. University Hospital of Marburg Germany. Research and Development Unit Parc Sanitari Sant Joan de Déu Cibersam ISCIII Barcelona Spain ICREA Pg. Lluis Companys 23 08010 Barcelona Spain. Department of Psychiatry University of Ottawa Ottawa ON Canada. Innovation in Mental and Physical Health and Clinical Treatment Strategic Research Centre School of Medicine Barwon Health Deakin University Geelong VIC Australia. Department of Pediatrics Yonsei University College of Medicine Seoul Republic of Korea. Department of Statistics Keimyung University Daegu Republic of Korea. Electronic address: nhson@kmu.ac.kr. Department of Psychiatry and the Institute of Behavioral Science in Medicine Yonsei University College of Medicine Seoul Republic of Korea. Electronic address: sanlee@yonsei.ac.kr.

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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Explainable AI: Definition and attributes of a good explanation for health AI

arXiv

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arXiv 2024年

作者： Kyrimi, Evangelia McLachlan, Scott Wohlgemut, Jared M. Perkins, Zane B. Lagnado, David A. Marsh, William Gimson, Alexander Shafti, Ali Ercole, Ari Banerjee, Amitava Glocker, Ben Schafer, Burkhard Gatsonis, Constantine Grosan, Crina Sent, Danielle Berman, David S. Glass, David O'Regan, Declan P. Letsios, Dimitrios Morrissey, Dylan Pisirir, Erhan Leofante, Francesco Soyel, Hamit Williamson, Jon Grieman, Keri Dube, Kudakwashe Mardsen, Max Nagendran, Myura Tai, Nigel Kostopoulou, Olga Jones, Owain Curzon, Paul Stoner, Rebecca S. Tandle, Sankalp Joshi, Shalmali Mossadegh, Somayyeh Buijsman, Stefan Miller, Tim Madai, Vince Istvan School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom School of Nursing Midwifery and Palliative Care King's College London London United Kingdom Centre for Trauma Sciences Blizard Institute Queen Mary University of London London United Kingdom Royal London Hospital Barts Health NHS Trust London United Kingdom Department of Experiment Psychology University College London London United Kingdom Cambridge Liver Unit Addenbrooke's Hospital Cambridge University Hospitals Hills Road Box 210 Cambridge United Kingdom University of Cambridge United Kingdom Cambridge Consultants Ltd. United Kingdom Division of Anaesthesia Cambridge Centre for AI in Medicine University of Cambridge Cambridge United Kingdom Magdelene College University of Cambridge United Kingdom Institute of Health Informatics University College London London United Kingdom Department of Computing Imperial College London London United Kingdom SCRIPT Centre for IT and IP Law School of Law University of Edinburgh United Kingdom Center for Statistical Sciences School of Public Health Brown University Providence United States Research Group Artificial Intelligence HU University of Applied Sciences Utrecht Netherlands Jheronimus Academy of Data Science Tilburg University Eindhoven University of Technology s-Hertogenbosch Netherlands Centre for Theoretical Physics Queen Mary University of London London United Kingdom School of Computing Ulster University Belfast United Kingdom MRC Laboratory of Medical Sciences Imperial College London London United Kingdom Department of Informatics King's College London United Kingdom Physiotherapy Department Barts Health NHS Trust London United Kingdom Sport and Exercise Medicine Queen Mary University of London London United Kingdom School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Department of Computing Imperial College London United Kingdom Departmen

Proposals of artificial intelligence (AI) solutions based on increasingly complex and accurate predictive models are becoming ubiquitous across many disciplines. As the complexity of these models grows, transparency and users' understanding often diminish. This suggests that accurate prediction alone is insufficient for making an AI-based solution truly useful. In the development of healthcare systems, this introduces new issues related to accountability and safety. Understanding how and why an AI system makes a recommendation may require complex explanations of its inner workings and reasoning processes. Although research on explainable AI (XAI) has significantly increased in recent years and there is high demand for XAI in medicine, defining what constitutes a good explanation remains ad hoc, and providing adequate explanations continues to be challenging. To fully realize the potential of AI, it is critical to address two fundamental questions about explanations for safety-critical AI applications, such as health-AI: (1) What is an explanation in health-AI? and (2) What are the attributes of a good explanation in health-AI? In this study, we examined published literature and gathered expert opinions through a two-round Delphi study. The research outputs include (1) a definition of what constitutes an explanation in health-AI and (2) a comprehensive list of attributes that characterize a good explanation in health-AI. © 2024, CC BY.

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