---
title: "NEJM AI 2024 — papers — Elamur Research"
description: "NEJM AI 2024 — papers: 1 paper in the Elamur Research library, with our summaries, ranked by citations."
canonical: "https://research.elamur.ai/free/en/venues/nejm-ai/2024/"
---
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# NEJM AI 2024 — papers

The works of NEJM AI published in 2024 that our library holds: 1 work, listed below with the most cited first; each has a page with our summary, its key points and its references.

[**98** works that year](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/nejm-ai/2024/#works) · [**57** citations of these works](https://md.research.elamur.ai/free/en/venues/nejm-ai/2024/#works)

## Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

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*

## All works of the year (98)

The most cited first; 1 with our summary link to their page here, the others to the original.

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*

[See all 98 papers in NEJM AI 2024 — papers →](https://md.research.elamur.ai/free/en/venues/nejm-ai/2024/papers/)

## Works with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. **[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/) [NEJM AI](https://md.research.elamur.ai/free/en/venues/nejm-ai/)**Tal Ifargan, Lukas Hafner, Maor Kern, et al.*2024 · 57 citations*

## Top topics

Topics of its works in our library, with the number of works on each.

[Language models & pretraining (1)](https://md.research.elamur.ai/free/en/topics/language-models/)

## Fields

[Arts and Humanities (1)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science (1)](https://md.research.elamur.ai/free/en/shelves/computer-science/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🎓**Technion – Israel Institute of Technology** Haifa · Israel 1 work here](https://md.research.elamur.ai/free/en/universities/technion-israel-institute-of-technology/)

works and citations from OpenAlex and our library.

- [← previous NEJM AI 2023](https://md.research.elamur.ai/free/en/venues/nejm-ai/2023/)
- [↑ back to NEJM AI](https://md.research.elamur.ai/free/en/venues/nejm-ai/)