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Alexander Hoffmann

ORCID: 0009-0007-8854-6487
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About
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A5101407985
Research Areas
  • International Arbitration and Investment Law
  • Corporate Governance and Law
  • European and International Law Studies
  • Corporate Governance and Management
  • Artificial Intelligence in Healthcare and Education
  • Digital Innovation in Industries
  • Law and Political Science
  • Linguistic Education and Pedagogy
  • Machine Learning in Healthcare
  • Corporate Management and Leadership
  • Biomedical Text Mining and Ontologies
  • Manufacturing Process and Optimization
  • Genomics and Rare Diseases
  • Topic Modeling
  • Semantic Web and Ontologies
  • Linguistic research and analysis
  • 3D Surveying and Cultural Heritage
  • Advanced Numerical Analysis Techniques
  • Innovation, Technology, and Society
  • Flexible and Reconfigurable Manufacturing Systems
  • Medical and Health Sciences Research
  • Global Health and Surgery
  • Libraries and Information Services
  • Electronic Health Records Systems
  • Biomedical and Engineering Education

Harvard University
 2023-2024

Harvard University Press
 2024

 To do no harm — and the most good — with AI in health care
OPENALEX - Publications 
Carey Beth Goldberg Laura Adams David Blumenthal Patrícia Flatley Brennan Noah Brown and 53 more Atul J. Butte Morgan Cheatham Dave deBronkart Jennifer Dixon Jeffrey M. Drazen Barbara J. Evans Sara M. Hoffman Chris Holmes Peter Lee Arjun K. Manrai Gilbert S. Omenn Jonathan B. Perlin Rachel Ramoni Guillermo Sapiro Rupa Sarkar Harpreet Sood Effy Vayena Isaac S. Kohane Emily Alsentzer Brian Anderson Ran D. Balicer Andrew L. Beam Erwin P. Böttinger Rebecca Weintraub Brendel Payal Chandak Arnaub K. Chatterjee Michael E. Chernew Antoine Duclos Lee A. Fleisher William J. Gordon Elizabeth A. Healey Alejandro Hernández-Arango Michele Kathleen Herndon Alexander Hoffmann Edward M. Hundert Indra Joshi Tobias Kowatsch Stephen J. Kraus Lisa Soleymani Lehmann Karim Lekadir Jean‐Louis Vincent Daniel J. Nigrin Reut Ohana Nigam H. Shah Haris Shuaib Tania Simoncelli Amelia L.M. Tan Donrich Thaldar Eugene Tunik Tommy Wang John Wilbanks Yuchen Xu Jianfei Zhao

10.1038/s41591-024-02853-7 article EN Nature Medicine 2024-02-22
 The potential of Generative Pre-trained Transformer 4 (GPT-4) to analyse medical notes in three different languages: a retrospective model-evaluation study
OPENALEX - Publications 
Maria Clara Saad Menezes Alexander Hoffmann Amelia L.M. Tan Mariné Nalbandyan Gilbert S. Omenn and 34 more Diego R. Mazzotti Alejandro Hernández-Arango Shyam Visweswaran Shruthi Venkatesh Kenneth D. Mandl Florence T. Bourgeois James W K Lee Andrew Makmur David A. Hanauer Michael G. Semanik Lauren T. Kerivan Terra Hill Julian Forero Carlos Alberto Velásquez Restrepo Matteo Vigna Piero Ceriana Noor Abu-El-Rub Paul Avillach Riccardo Bellazzi Thomas Callaci Alba Gutiérrez‐Sacristán Alberto Malovini Jomol Mathew Michele Morris Venkatesh L. Murthy Tommaso Mario Buonocore Enea Parimbelli Lav P. Patel Carlos Sáez Malarkodi Jebathilagam Samayamuthu Jeffrey Thompson Valentina Tibollo Zongqi Xia Isaac S. Kohane

10.1016/s2589-7500(24)00246-2 article EN The Lancet Digital Health 2024-12-24
 Implications of mappings between International Classification of Diseases clinical diagnosis codes and Human Phenotype Ontology terms
OPENALEX - Publications 
Amelia L.M. Tan Rafael S. Gonçalves William Yuan Gabriel A. Brat Robert Gentleman and 95 more Isaac S. Kohane Aaron J. Masino Adeline Makoudjou Adem Albayrak Alba Gutiérrez‐Sacristán Alberto Zambelli Alberto Malovini Aldo Carmona Alexander Hoffmann Alexandre Gramfort Alon Geva Alvar Blanco-Martínez Amelia L.M. Tan Ana I. Terriza-Torres Anastassia Spiridou Andrea Prunotto Andrew M. South Andrew K. Vallejos Andrew Atz Anita Burgun Anna Alloni Anna Maria Cattelan Anne‐Sophie Jannot Antoine Neuraz Antonio Bellasi Anupama Maram Arianna Dagliati Arnaud Sandrin Arnaud Serret-Larmande Arthur Mensch Ashley Pfaff Ashley Batugo Ashok Krishnamurthy Atif Adam Audrey Dionne Batsal Devkota Bertrand Moal Bing He Brendin R. Beaulieu‐Jones Brett K. Beaulieu‐Jones Brian D. Ostasiewski Bruce J. Aronow Bryce W. Q. Tan Byorn W L Tan Carlo Torti Carlos Sáez Carlos Tadeu Breda Neto Charles Sonday Charlotte Caucheteux Chengsheng Mao Chiara Zucco Christel Daniel Christian Haverkamp Chuan Hong Clara-Lea Bonzel Cinta Moraleda Damien Leprovost Daniel Key Daniela Zöller Danielle Pillion Danielle L. Mowery Danilo F Amendola Darren W. Henderson David A. Hanauer Deanne Taylor Demián Wassermann Derek Hazard Detlef Kraska Diego R. Mazzotti Domenick Silvio Douglas S. Bell Douglas A. Murad Elisa Salamanca Emily Bucholz Emily Getzen Emily Pfaff Emily Schriver Emma M. S. Toh Enea Parimbelli Enrico M Trecarichi Fatima Ashraf Fernando J Sanz Vidorreta Florence T. Bourgeois Francesca Sperotto François Angoulvant Gabriel A. Brat Gaël Varoquaux Gilbert S. Omenn Giuseppe Agapito Giuseppe Albi Griffin M. Weber Guillaume Verdy Guillaume Lemaître Gustavo Roig-Domínguez Hans U Prokosch

Abstract Objective Integrating electronic health record (EHR) data with other resources is essential in rare disease research due to low prevalence. Such integration dependent on the alignment of ontologies used for annotation. The international classification diseases (ICD) annotate clinical diagnoses, while human phenotype ontology (HPO) phenotypes. Although these overlap biomedical entities they describe, extent which are interoperable unknown. We investigate how well aligned and whether...

10.1093/jamiaopen/ooae118 article EN cc-by JAMIA Open 2024-10-08
 Assessing the Potential of GPT-4 to Annotate Medical Notes Across Different Languages and Countries: A Model Evaluation Study
OPENALEX - Publications 
Maria Clara Saad Menezes Alexander Hoffmann Amelia L.M. Tan Mariné Nalbandyan Gilbert S. Omenn and 34 more Diego R. Mazzotti Alejandro Hernández-Arango Shyam Visweswaran Shruthi Venkatesh Kenneth D. Mandl Florence T. Bourgeois James W K Lee Andrew Makmur David A. Hanauer Michael G. Semanik Lauren T. Kerivan Terra Hill Julian Forero Carlos Andrés CR Restrepo Castro Matteo Vigna Piero Ceriana Noor Abu-El-Rub Paul Avillach Riccardo Bellazzi Thomas Callaci Alba Gutiérrez‐Sacristán Alberto Malovini Jomol Mathew Michele Morris Venkatesh L. Murthy Enea Parimbelli Lav P. Patel Carlos Sáez Malarkodi Jebathilagam Samayamuthu Jeffrey Thompson Valentina Tibollo Zongqi Xia Isaac S. Kohane The Consortium for Clinical Characterization of COVID- by EHR

Background: Physicians invest hours creating patient notes, which are rich in information but difficult for computers to analyze due their unstructured format. GPT-4 reshaped our ability process text, yet it is unknown how well this model can handle medical notes. This project aims compare GPT-4's annotate notes against experienced physicians across three different languages at multiple institutions and countries. Methods: study included eight sites from four countries - the United States,...

10.2139/ssrn.4823631 preprint EN 2024-01-01
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