Fetching the paper…
Reading the bibliography…
An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures.
“Reasoning foundations of medical diagnosis: symbolic logic, probability, and value theory aid our understanding of how physicians reason”
Robert Ledley and Lee Lusted · 1959
Earlier work this paper cites.
“Categorical and probabilistic reasoning in medical diagnosis”
Peter Szolovits and Stephen Pauker · 1978
Earlier work this paper cites.
“Internist-I, an experimental computer-based diagnostic consultant for general internal medicine”
Randolph Miller, Harry Pople and Jack Myers · 1985
Earlier work this paper cites.
“Differential diagnosis generators: an evaluation of currently available computer programs”
William Bond, Linda Schwartz, Kevin Weaver, Donald Levick, Michael Giuliano and Mark Graber · 2012
Earlier work this paper cites.
“The quadruple aim: care, health, cost and meaning in work”
Rishi Sikka, Julianne Morath and Lucian Leape · 2015
Earlier work this paper cites.
“MIMIC-III, a freely accessible critical care database”
Alistair Johnson, Tom Pollard, Lu Shen, Li-wei Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony and Roger Mark · 2016
Earlier work this paper cites.
“Dissecting racial bias in an algorithm used to manage the health of populations”
Ziad Obermeyer, Brian Powers, Christine Vogeli and Sendhil Mullainathan · 2019
Earlier work this paper cites.
“" Hello AI": uncovering the onboarding needs of medical practitioners for human-AI collaborative decision-making”
Carrie Cai, Samantha Winter, David Steiner, Lauren Wilcox and Michael Terry · 2019
Earlier work this paper cites.
“A deep learning system for differential diagnosis of skin diseases”
Yuan Liu, Ayush Jain, Clara Eng, David Way, Kang Lee, Peggy Bui, Kimberly Kanada, Guilherme de Oliveira, Jessica Gallegos and Sara Gabriele · 2020
Earlier work this paper cites.
“Artificial intelligence system approaching neuroradiologist-level differential diagnosis accuracy at brain MRI”
Andreas Rauschecker, Jeffrey Rudie, Long Xie, Jiancong Wang, Michael Duong, Emmanuel Botzolakis, Asha Kovalovich, John Egan, Tessa Cook and R Bryan · 2020
Earlier work this paper cites.
“Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis”
Urs Muehlematter, Paola Daniore and Kerstin Vokinger · 2021
Earlier work this paper cites.
“Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations”
Laleh Seyyed-Kalantari, Haoran Zhang, Matthew McDermott, Irene Chen and Marzyeh Ghassemi · 2021
Earlier work this paper cites.
“Do as AI say: susceptibility in deployment of clinical decision-aids”
Susanne Gaube, Harini Suresh, Martina Raue, Alexander Merritt, Seth Berkowitz, Eva Lermer, Joseph Coughlin, John Guttag, Errol Colak and Marzyeh Ghassemi · 2021
Cited alongside, same era.
“Bloom: A 176b-parameter open-access multilingual language model”
Teven Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Luccioni, François Yvon and Matthias Gallé · 2022
Cited alongside, same era.
“Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task”
Jannik Kossen, Cătălina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev and Danielle Belgrave · 2022
Cited alongside, same era.
“Evaluation of medical decision support systems (DDX generators) using real medical cases of varying complexity and origin”
Peter Fritz, Andreas Kleinhans, R Raoufi, A Sediqi, Nico Schmid, Severin Schricker, Moritz Schanz, Christine Fritz-Kuisle, P Dalquen and H Firooz · 2022
Cited alongside, same era.
“Capabilities of gpt-4 on medical challenge problems”
Harsha Nori, Nicholas King, Scott McKinney, Dean Carignan and Eric Horvitz · 2023
Closest in time.
“Use of GPT-4 to Diagnose Complex Clinical Cases”
Alexander. Eriksen, Soren Moller and Ryg · 2023
Closest in time.
“Accuracy of a Vision-Language Model on Challenging Medical Cases”, 2023
Thomas Buckley, James. Diao, Adam Rodman and Arjun. Manrai · 2023
Closest in time.
“Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations”
Joey Hong, Sergey Levine and Anca Dragan · 2023
Closest in time.
“Generative Relevance Feedback with Large Language Models”
Iain Mackie, Shubham Chatterjee and Jeffrey Dalton · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
“Overbooked and overlooked: machine learning and racial bias in medical appointment scheduling”
Michele Samorani, Shannon Harris, Linda Blount, Haibing Lu and Michael Santoro · 2022
Cited alongside, same era.
“Conversational ai models for ophthalmic diagnosis: Comparison of chatgpt and the isabel pro differential diagnosis generator”
Michael Balas and Edsel Ing · 2023
Cited alongside, same era.
“Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge”
Zahir Kanjee, Byron Crowe and Adam Rodman · 2023
Cited alongside, same era.
“GPT-4 Technical Report”, 2023
OpenAI · 2023
Cited alongside, same era.
Rohan Anil, Andrew Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey and Zhifeng Chen · 2023
Cited alongside, same era.
“Llama 2: Open foundation and fine-tuned chat models”
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava and Shruti Bhosale · 2023
Cited alongside, same era.
“Large language models encode clinical knowledge”
Karan Singhal, Shekoofeh Azizi, Tao Tu, S Mahdavi, Jason Wei, Hyung Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis and Stephen Pfohl · 2023
Cited alongside, same era.
Closest in time.
“Llava-med: Training a large language-and-vision assistant for biomedicine in one day”
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon and Jianfeng Gao · 2023
Closest in time.
“Towards generalist biomedical ai”
Tao Tu, Shekoofeh Azizi, Danny Driess, Mike Schaekermann, Mohamed Amin, Pi-Chuan Chang, Andrew Carroll, Chuck Lau, Ryutaro Tanno and Ira Ktena · 2023
Closest in time.
“Automatic correction of performance drift under acquisition shift in medical image classification”
Mélanie Roschewitz, Galvin Khara, Joe Yearsley, Nisha Sharma, Jonathan James, Éva Ambrózay, Adam Heroux, Peter Kecskemethy, Tobias Rijken and Ben Glocker · 2023
Closest in time.
“Med-halt: Medical domain hallucination test for large language models”
Logesh Umapathi, Ankit Pal and Malaikannan Sankarasubbu · 2023
Closest in time.
“Do Large Language Models Know What They Don’t Know?”
Zhangyue Yin, Qiushi Sun, Qipeng Guo, Jiawen Wu, Xipeng Qiu and Xuanjing Huang · 2023
Closest in time.
“Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians”
Krishnamurthy Dvijotham, Jim Winkens, Melih Barsbey, Sumedh Ghaisas, Robert Stanforth, Nick Pawlowski, Patricia Strachan, Zahra Ahmed, Shekoofeh Azizi and Yoram Bachrach · 2023
Closest in time.