Welcome to Hipócrates 3.0! In this episode, we explore an innovative study published this year in the Journal of Medical Internet Research (IF 7.4) that puts artificial intelligence, specifically ChatGPT’s GPT-4, head-to-head with resident physicians in diagnosing medical emergencies. Developed by OpenAI, GPT-4 has proven to be a promising tool, surpassing both its predecessor, GPT-3.5, and resident physicians in diagnostic accuracy for internal medicine cases.

We discuss the study’s surprising results, its implications for the future of medicine, and how AI can be an essential ally in clinical practice. And for those of you striving to pass Step 1, we’ve included a message of encouragement and a shout-out to the amazing USMLE Privateers group for their unwavering support. Press play and join us as we dive into the impact of AI in healthcare!

John Michael Hoppe, et al. ChatGPT with GPT-4 Outperforms Emergency Department Physicians in Diagnostic Accuracy: Retrospective Analysis. Journal of Medical Internet Research, vol. 26, 8 July 2024, pp. e56110–e56110, https://doi.org/10.2196/56110.

Have you ever read scientific articles with titles like 'Differential diagnosis of secondary hypertension based on deep learning' and wondered what this has to do with medicine? It seems like a combination of medical terms you know well, mixed with words like 'Machine Learning' and 'Artificial Neural Network.' But let me clarify: this title is real. It comes from a 2023 article published in the scientific journal 'Artificial Intelligence in Medicine.' Artificial intelligence is not a distant concept; it's a reality that is already part of serious medical research. If you've learned how to perform sutures and solve complex diagnoses, then understanding AI and concepts like Machine Learning is just another challenge you are fully capable of meeting. In the next episode of Hippocrates 3.0, we will decode these terms and show how they are revolutionizing the medical field. And the best part: it's straightforward. Follow us on Spotify or your favorite podcast platform and find out how these technologies are much closer to your daily medical practice than you might think. Prepare for an episode that will open your eyes to the future of medicine that is already here.

1) A systematic literature review of machine learning based risk prediction models for diabetic retinopathy progression:

https://pubmed.ncbi.nlm.nih.gov/37673580/

2) Differential diagnosis of secondary hypertension based on deep learning

https://pubmed.ncbi.nlm.nih.gov/37295898/

3) Gynecological cancer prognosis using machine learning techniques: A systematic review of the last three decades (1990-2022) https://pubmed.ncbi.nlm.nih.gov/37100507/

Journal: Artificial Intelligence in Medicine https://www.sciencedirect.com/journal/artificial-intelligence-in-medicine

Follow me on instagram: @drthiagoflorencio.ia