---
title: "NEJM AI 2024 — all accepted papers — the most cited first"
description: "All 98 papers of NEJM AI 2024, the most cited first; those with our summary link to it. Among them: Towards Generalist Biomedical AI ↗."
canonical: "https://research.elamur.ai/free/en/venues/nejm-ai/2024/papers/"
---
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# NEJM AI 2024: all accepted papers

98 papers · the most cited first · [← NEJM AI 2024](https://md.research.elamur.ai/free/en/venues/nejm-ai/2024/)

1. **[Towards Generalist Biomedical AI ↗](https://doi.org/10.1056/aioa2300138)**Tao Tu, Shekoofeh Azizi, Danny Driess et al.*452 citations*
2. **[Almanac — Retrieval-Augmented Language Models for Clinical Medicine ↗](https://doi.org/10.1056/aioa2300068)**Cyril Zakka, Rohan Shad, Akash R. Chaurasia et al.*405 citations*
3. **[A Multimodal Biomedical Foundation Model Trained from Fifteen Million Image–Text Pairs ↗](https://doi.org/10.1056/aioa2400640)**Sheng Zhang, Yanbo Xu, Naoto Usuyama et al.*270 citations*
4. **[Can Large Language Models Provide Useful Feedback on Research Papers? A Large-Scale Empirical Analysis](https://md.research.elamur.ai/free/en/papers/liang-2023-large-language-models-provide/)**Weixin Liang, Yuhui Zhang, Hancheng Cao et al.*243 citations · our summary*
5. **[Large Language Models Are Poor Medical Coders — Benchmarking of Medical Code Querying ↗](https://doi.org/10.1056/aidbp2300040)**Ali Soroush, Benjamin Scott Glicksberg, Eyal Zimlichman et al.*136 citations*
6. **[GPT versus Resident Physicians — A Benchmark Based on Official Board Scores ↗](https://doi.org/10.1056/aidbp2300192)**Uriel Katz, Eran Cohen, Eliya K. Shachar et al.*134 citations*
7. **[Retrieval-Augmented Generation–Enabled GPT-4 for Clinical Trial Screening ↗](https://doi.org/10.1056/aioa2400181)**Ozan Ünlü, Jiyeon Shin, Charlotte J. Mailly et al.*114 citations*
8. **[Comparative Evaluation of LLMs in Clinical Oncology ↗](https://doi.org/10.1056/aioa2300151)**Nicholas Robert Rydzewski, Deepak Dinakaran, Shuang George Zhao et al.*106 citations*
9. **[RAG in Health Care: A Novel Framework for Improving Communication and Decision-Making by Addressing LLM Limitations ↗](https://doi.org/10.1056/aira2400380)**Karen Ka Yan Ng, Izuki Matsuba, Peter Chengming Zhang*103 citations*
10. **[Benchmarking Open-Source Large Language Models, GPT-4 and Claude 2 on Multiple-Choice Questions in Nephrology ↗](https://doi.org/10.1056/aidbp2300092)**Sean Wu, Michael Koo, Lesley Blum et al.*97 citations*
11. **[GPT-4 for Information Retrieval and Comparison of Medical Oncology Guidelines ↗](https://doi.org/10.1056/aics2300235)**Dyke Ferber, Isabella C. Wiest, Georg Wölflein et al.*90 citations*
12. **[Using ChatGPT to Facilitate Truly Informed Medical Consent ↗](https://doi.org/10.1056/aics2300145)**Fatima Nadeem Mirza, Oliver Young Tang, Ian David Connolly et al.*88 citations*
13. **[Development and Validation of a Multimodal Multitask Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence ↗](https://doi.org/10.1056/aioa2300221)**Jianing Qiu, Jian Wu, Hao Wei et al.*79 citations*
14. **[Evaluation of Sepsis Prediction Models before Onset of Treatment ↗](https://doi.org/10.1056/aioa2300032)**Fahad Kamran, Donna Tjandra, Andrew Heiler et al.*73 citations*
15. **[FDA-Authorized AI/ML Tool for Sepsis Prediction: Development and Validation ↗](https://doi.org/10.1056/aioa2400867)**Akhil Bhargava, Carlos G. Lopez-Espina, Lee Schmalz et al.*72 citations*
16. **[A Call for Artificial Intelligence Implementation Science Centers to Evaluate Clinical Effectiveness ↗](https://doi.org/10.1056/aip2400223)**Chris Longhurst, Karandeep Singh, Aneesh Chopra et al.*66 citations*
17. **[CORAL: Expert-Curated Oncology Reports to Advance Language Model Inference ↗](https://doi.org/10.1056/aidbp2300110)**Madhumita Sushil, Vanessa Elaine Kennedy, Divneet Mandair et al.*61 citations*
18. **[To Do No Harm — and the Most Good — with AI in Health Care ↗](https://doi.org/10.1056/aip2400036)**Carey Beth Goldberg, Laura L. Adams, David Blumenthal et al.*61 citations*
19. **[Does AI-Powered Clinical Documentation Enhance Clinician Efficiency? A Longitudinal Study ↗](https://doi.org/10.1056/aioa2400659)**Tsai‐Ling Liu, Timothy C. Hetherington, Ajay Dharod et al.*60 citations*
20. **[Medical Ethics of Large Language Models in Medicine ↗](https://doi.org/10.1056/aira2400038)**Jasmine Chiat Ling Ong, Yin‐Hsi Chang, William Wasswa et al.*58 citations*
21. **[Zero-Shot Clinical Trial Patient Matching with LLMs ↗](https://doi.org/10.1056/aics2400360)**Michael Wornow, Alejandro Lozano, Dev Dash et al.*57 citations*
22. **[Large Language Models for More Efficient Reporting of Hospital Quality Measures ↗](https://doi.org/10.1056/aics2400420)**Aaron E. Boussina, Rishivardhan Krishnamoorthy, Kimberly Quintero et al.*55 citations*
23. **[Artificial Intelligence–Powered Rapid Identification of ST-Elevation Myocardial Infarction via Electrocardiogram (ARISE) — A Pragmatic Randomized Controlled Trial ↗](https://doi.org/10.1056/aioa2400190)**Chin S. Lin, Wei-Ting Liu, Chiao‐Hsiang Chang et al.*54 citations*
24. **[The Regulation of Clinical Artificial Intelligence ↗](https://doi.org/10.1056/aipc2400545)**David Blumenthal, Bakul Patel*54 citations*
25. **[AI-MARRVEL — A Knowledge-Driven AI System for Diagnosing Mendelian Disorders ↗](https://doi.org/10.1056/aioa2300009)**Dongxue Mao, Chaozhong Liu, Linhua Wang et al.*50 citations*
26. **[Cognitive Biases and Artificial Intelligence ↗](https://doi.org/10.1056/aics2400639)**Jonathan Wang, Donald A. Redelmeier*42 citations*
27. **[Clinical Text Datasets for Medical Artificial Intelligence and Large Language Models — A Systematic Review ↗](https://doi.org/10.1056/aira2400012)**Jiageng Wu, Xiaocong Liu, Minghui Li et al.*41 citations*
28. **[GPT-4 in a Cancer Center — Institute-Wide Deployment Challenges and Lessons Learned ↗](https://doi.org/10.1056/aics2300191)**Renato Umeton, Anne Kwok, Rahul Maurya et al.*36 citations*
29. **[FHIR-GPT Enhances Health Interoperability with Large Language Models ↗](https://doi.org/10.1056/aics2300301)**Yikuan Li, Hanyin Wang, Halid Ziya Yerebakan et al.*34 citations*
30. **[How Academic Medical Centers Govern AI Prediction Tools in the Context of Uncertainty and Evolving Regulation ↗](https://doi.org/10.1056/aip2300048)**Paige Nong, Reema Hamasha, Karandeep Singh et al.*34 citations*
31. **[Autonomous LLM-Driven Research — from Data to Human-Verifiable Research Papers](https://md.research.elamur.ai/free/en/papers/ifargan-2024-autonomous-llm-driven-research/)**Tal Ifargan, Lukas Hafner, Maor Kern et al.*33 citations · our summary*
32. **[Rubrics to Prompts: Assessing Medical Student Post-Encounter Notes with AI ↗](https://doi.org/10.1056/aics2400631)**Andrew R. Jamieson, Michael J. Holcomb, Thomas O. Dalton et al.*33 citations*
33. **[Improving Clinician Performance in Classifying EEG Patterns on the Ictal–Interictal Injury Continuum Using Interpretable Machine Learning ↗](https://doi.org/10.1056/aioa2300331)**Alina Jade Barnett, Zhicheng Guo, Jin Jing et al.*32 citations*
34. **[Evaluation of AI Solutions in Health Care Organizations — The OPTICA Tool ↗](https://doi.org/10.1056/aics2300269)**Noa Dagan, Stav Devons-Sberro, Ziv Paz et al.*30 citations*
35. **[Scaling Adoption of Medical AI — Reimbursement from Value-Based Care and Fee-for-Service Perspectives ↗](https://doi.org/10.1056/aipc2400083)**Michael D. Abràmoff, Tinglong Dai, James Zou*30 citations*
36. **[We Need More Randomized Clinical Trials of AI ↗](https://doi.org/10.1056/aie2400881)**David Ouyang, Joseph W. Hogan*24 citations*
37. **[Combining Multiple Large Language Models Improves Diagnostic Accuracy ↗](https://doi.org/10.1056/aics2400502)**Gioele Barabucci, Victor Shia, Eugene A. Chu et al.*23 citations*
38. **[PROTEUS: A Prospective RCT Evaluating Use of AI in Stress Echocardiography ↗](https://doi.org/10.1056/aioa2400865)**Ross Upton, Ashley Paul Akerman, Thomas Hugh Marwick et al.*21 citations*
39. **[AI-Based Anomaly Detection for Clinical-Grade Histopathological Diagnostics ↗](https://doi.org/10.1056/aioa2400468)**Jonas Dippel, Niklas Prenißl, Julius Hense et al.*20 citations*
40. **[National Use of Artificial Intelligence for Eye Screening in Singapore ↗](https://doi.org/10.1056/aics2400404)**Dinesh Visva Gunasekeran, Steven Miller, Wynne Hsu et al.*20 citations*
41. **[Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities ↗](https://doi.org/10.1056/aioa2400018)**Sahar Kazemzadeh, Atilla P. Kiraly, Zaid Nabulsi et al.*20 citations*
42. **[The Chief Health AI Officer — An Emerging Role for an Emerging Technology ↗](https://doi.org/10.1056/aip2400109)**Ashley Beecy, Chris Longhurst, Karandeep Singh et al.*20 citations*
43. **[Fine-Tuning LLMs with Medical Data: Can Safety Be Ensured? ↗](https://doi.org/10.1056/aics2400390)**Minkyoung Kim, Yunha Kim, Hee Jun Kang et al.*19 citations*
44. **[Prospective Evaluation of Machine Learning for Public Health Screening: Identifying Unknown Hepatitis C Carriers ↗](https://doi.org/10.1056/aioa2300012)**Noa Dagan, Ori Magen, Michael Leshchinsky et al.*19 citations*
45. **[Cognitive Bias in Large Language Models: Implications for Research and Practice ↗](https://doi.org/10.1056/aie2400961)**Laura Zwaan*17 citations*
46. **[How Generalizable Are Foundation Models When Applied to Different Demographic Groups and Settings? ↗](https://doi.org/10.1056/aics2400497)**Zhuxin Xiong, Xiaofei Wang, Yukun Zhou et al.*17 citations*
47. **[Evolution of Future Medical AI Models — From Task-Specific, Disease-Centric to Universal Health ↗](https://doi.org/10.1056/aip2400289)**Weizhi Ma, Bin Sheng, Yang Liu et al.*16 citations*
48. **[External Validation of a Commercial Acute Kidney Injury Predictive Model ↗](https://doi.org/10.1056/aioa2300099)**Sayon Dutta, Dustin S. McEvoy, Lisette N. Dunham et al.*16 citations*
49. **[The EU AI Act: Implications for U.S. Health Care ↗](https://doi.org/10.1056/aip2400449)**Sebastian Porsdam Mann, Ivan Glenn Cohen, Timo Minssen*16 citations*
50. **[Preparing for the Widespread Adoption of Clinic Visit Recording ↗](https://doi.org/10.1056/aip2400392)**Paul James Barr, Robert E. Gramling, Soroush Vosoughi*15 citations*
51. **[Trustworthy Evaluation of Clinical AI for Analysis of Medical Images in Diverse Populations ↗](https://doi.org/10.1056/aioa2400353)**Jiri Fajtl, Roshan A. Welikala, Sarah Ann Barman et al.*15 citations*
52. **[When the Model Trains You: Induced Belief Revision and Its Implications on Artificial Intelligence Research and Patient Care — A Case Study on Predicting Obstructive Hydronephrosis in Children ↗](https://doi.org/10.1056/aics2300004)**Jethro C.C. Kwong, David‐Dan Nguyen, Adree Khondker et al.*15 citations*
53. **[Artificial Intelligence Identifies Factors Associated with Blood Loss and Surgical Experience in Cholecystectomy ↗](https://doi.org/10.1056/aioa2300088)**Josiah G. Aklilu, Min Sun, Shelly Goel et al.*14 citations*
54. **[GPT-4 Performance, Nondeterminism, and Drift in Genetic Literature Review ↗](https://doi.org/10.1056/aics2400245)**Samuel Aronson, Kalotina Machini, Jiyeon Shin et al.*14 citations*
55. **[Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations ↗](https://doi.org/10.1056/aip2401088)**Joseph Edward Alderman, Joanne Palmer, Elinor Laws et al.*14 citations*
56. **[Trials of AI Interventions Must Be Preregistered ↗](https://doi.org/10.1056/aie2400146)**Jeffrey M. Drazen, Charlotte J. Haug*14 citations*
57. **[AI as an Ecosystem — Ensuring Generative AI Is Safe and Effective ↗](https://doi.org/10.1056/aip2400611)**Enrico W Coiera, David Fraile Navarro*12 citations*
58. **[Advancing Diabetic Macular Edema Detection from 3D Optical Coherence Tomography Scans: Integrating Privacy-Preserving AI and Generalizability Techniques — A Prospective Validation in Vietnam ↗](https://doi.org/10.1056/aioa2400091)**Truong Nguyen, Meirui Jiang, Dawei Yang et al.*11 citations*
59. **[Disorder-Free Data Are All You Need — Inverse Supervised Learning for Broad-Spectrum Head Disorder Detection ↗](https://doi.org/10.1056/aioa2300137)**Yuwei He, Yuchen Guo, Jinhao Lyu et al.*11 citations*
60. **[The U.S. President’s Executive Order on Artificial Intelligence ↗](https://doi.org/10.1056/aipc2300296)**David Blumenthal*11 citations*
61. **[Validation of a Mobile App for Remote Autism Screening in Toddlers ↗](https://doi.org/10.1056/aics2400510)**Pradeep Raj Krishnappa Babu, J. Matías Di Martino, Rachel E. Aiello et al.*11 citations*
62. **[Co-creating Consent for Data Use — AI-Powered Ethics for Biomedical AI ↗](https://doi.org/10.1056/aipc2400237)**Barbara J. Evans, Azra Bihorac*10 citations*
63. **[If Machines Exceed Us: Health Care at an Inflection Point ↗](https://doi.org/10.1056/aip2400559)**Eyal Klang, Idit Tessler, Robert Freeman et al.*10 citations*
64. **[Spending Analysis of Machine Learning–Based Communication Nudges in Oncology ↗](https://doi.org/10.1056/aioa2300228)**Tej A. Patel, Jonathan R. Heintz, Jinbo Chen et al.*10 citations*
65. **[Ethical Oversight of Data Science Health Research in Africa ↗](https://doi.org/10.1056/aipc2400033)**Clement Adebamowo, Shawneequa Callier, Oluchi Christiana Maduka et al.*9 citations*
66. **[Large Language Models Seem Miraculous, but Science Abhors Miracles ↗](https://doi.org/10.1056/aip2300103)**Peter Szolovits B*9 citations*
67. **[Patient Portal — When Patients Take AI into Their Own Hands ↗](https://doi.org/10.1056/aip2400283)**Carey Beth Goldberg*9 citations*
68. **[Ethical Use of Artificial Intelligence in Medical Diagnostics Demands a Focus on Accuracy, Not Fairness ↗](https://doi.org/10.1056/aip2400672)**Mert Rory Sabuncu, Alan Q. Wang, Minh Nguyen*8 citations*
69. **[Four-Channel ECG as a Single Source for Early Diagnosis of Cardiac Hypertrophy and Dilation — A Deep Learning Approach ↗](https://doi.org/10.1056/aioa2300297)**Hongling Zhu, Yinuo Jiang, Cheng Cheng et al.*8 citations*
70. **[Health Care Cost Reductions with Machine Learning–Directed Evaluations during Radiation Therapy — An Economic Analysis of a Randomized Controlled Study ↗](https://doi.org/10.1056/aioa2300118)**Divya Natesan, Eric L. Eisenstein, Samantha Marie Thomas et al.*8 citations*
71. **[Managing Patient Use of Generative Health AI ↗](https://doi.org/10.1056/aipc2400927)**David Blumenthal, Carey Beth Goldberg*8 citations*
72. **[Machine Learning to Infer a Health State Using Biomedical Signals — Detection of Hypoglycemia in People with Diabetes while Driving Real Cars ↗](https://doi.org/10.1056/aioa2300013)**Vera Franziska Lehmann, Thomas Züger, Martin Maritsch et al.*7 citations*
73. **[The Impact of Task Set-up in Algorithm Design: Regression versus Classification ↗](https://doi.org/10.1056/aics2300176)**Amey Vrudhula, John Weston Hughes, Neal Yuan et al.*7 citations*
74. **[Do We Need Data Standards in the Era of Large Language Models? ↗](https://doi.org/10.1056/aie2400548)**Gabriel A. Brat, Joshua C. Mandel, Matthew B. A. McDermott*6 citations*
75. **[Settling the Score on Algorithmic Discrimination in Health Care ↗](https://doi.org/10.1056/aip2400583)**Marzyeh Ghassemi, Maia Hightower, Elaine Okanyene Nsoesie*6 citations*
76. **[A New Foundation Model for Multimodal Ophthalmic Images: Advancing Disease Detection and Prediction ↗](https://doi.org/10.1056/aie2401024)**Mark A. Chia, Yukun Zhou, Pearse Andrew Keane*5 citations*
77. **[AI-RISE to the Challenge — Artificial Intelligence Reduces Time to Treatment in STEMI ↗](https://doi.org/10.1056/aie2400472)**Robert Avram, William Fuller Fearon*5 citations*
78. **[Artificial Intelligence–Based Copilots to Generate Causal Evidence ↗](https://doi.org/10.1056/aip2400727)**Maya L. Petersen, Ahmed M. Alaa, Emre Kıcıman et al.*5 citations*
79. **[Exploring the Past — and Future — of Medical Diagnosis and Artificial Intelligence ↗](https://doi.org/10.1056/aip2400707)**Adam M. Rodman, Andrew L. Beam, Arjun Kumar Manrai*5 citations*
80. **[Histopathology Slide Indexing and Search — Are We There Yet? ↗](https://doi.org/10.1056/aics2300019)**Helen H. Shang, Mohammad Sadegh Nasr, Jai Prakash Veerla et al.*5 citations*
81. **[Policy in Progress — The Race to Frame AI in Health Care ↗](https://doi.org/10.1056/aie2400044)**Isaac S. Kohane*5 citations*
82. **[What We Want to Publish at NEJM AI ↗](https://doi.org/10.1056/aie2300304)**Arjun Kumar Manrai, Andrew L. Beam, Isaac S. Kohane*5 citations*
83. **[Why Medicine Must Become a Knowledge-Processing Discipline ↗](https://doi.org/10.1056/aip2400582)**Isaac S. Kohane, Andrew L. Beam, Arjun Kumar Manrai*5 citations*
84. **[A Global Health Data Divide ↗](https://doi.org/10.1056/aie2400388)**Xiaoxuan Liu, Joseph Edward Alderman, Elinor Laws*4 citations*
85. **[Mary Steps Out: Capturing Patient Experience through Qualitative and AI Methods ↗](https://doi.org/10.1056/aip2400567)**Valerie J. Renard, Marianna D. LaNoue, Truls Østbye et al.*4 citations*
86. **[The Promise and Perils of Autonomous AI in Science ↗](https://doi.org/10.1056/aie2401073)**Junyi Gao, Ewen Munro Harrison*3 citations*
87. **[The Role of Health Data Utilities in Supporting Health AI ↗](https://doi.org/10.1056/aipc2400401)**Ahmad Alkasir, Gabriel Seidman, Jolie Ritzo et al.*3 citations*
88. **[Who’s Training Whom? ↗](https://doi.org/10.1056/aip2400006)**Jonathan H. Chen*3 citations*
89. **[AI for Oncology Drug Data Harmonization — Amazon versus OpenAI ↗](https://doi.org/10.1056/aics2400661)**Jay G. Ronquillo, Brett R. South, Timothy Lee Wiemken et al.*2 citations*
90. **[AI-Based Diabetic Macular Edema Screening for Improved Care in Low-Resource Settings ↗](https://doi.org/10.1056/aie2400698)**Tien‐En Tan, Zhen Ling Teo, Stela Vujosevic et al.*1 citation*
91. **[Advancing Autism Detection: A Digital Step Forward ↗](http://dx.doi.org/10.1056/aie2400811)**Isaac S. Kohane*1 citation*
92. **[Disorder-Free Data Are All You Need — Inverse Supervised Learning for Broad-Spectrum Head Disorder Detection ↗](http://dx.doi.org/10.1056/aix2400504)***1 citation*
93. **[Human-in-the-Loop AI Summaries of NEJM AI Grand Rounds ↗](https://doi.org/10.1056/aie2400581)**Arjun Kumar Manrai, Andrew L. Beam*1 citation*
94. **[Pixels and Pitfalls: Building Robust Artificial Intelligence for Medical Imaging ↗](https://doi.org/10.1056/aip2400803)**Pranav Rajpurkar, Andrew L. Beam, Arjun Kumar Manrai*1 citation*
95. **[Reclaiming Voice with AI ↗](https://doi.org/10.1056/aip2401000)**Fatima Nadeem Mirza, Alexis Bogan, Andrew L. Beam et al.*1 citation*
96. **[A Letter about “Evaluation of Sepsis Prediction Models before Onset of Treatment” ↗](https://doi.org/10.1056/aip2400247)**Jeffrey M. Feit
97. **[Are Stronger Feature Representations All You Need for Histology Image Search? ↗](https://doi.org/10.1056/aie2400314)**Richard J. Chen, Faisal Mahmood
98. **[Four-Channel ECG as a Single Source for Early Diagnosis of Cardiac Hypertrophy and Dilation — A Deep Learning Approach ↗](https://doi.org/10.1056/aix2401111)**
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