Medical Attention

<p>Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.</p> <p>00:35 - Scaling Large Language Models for Next-Generation Single-Cell Analysis</p> <p> </p>...

<p>This episode, we discuss some of the challenges in using large language models (LLMs) for the task of summarising inpatient encounters. </p> 00:30 - Technical wrap - new models, MiT’s State of AI in Business 2025...

<p>Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.</p> <p>00:30 - Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a...

<p>Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.</p> 00:30 - An Electrocardiogram Foundation Model Built on over 10 Million Recordings 07:10 - Zero-shot...

<p>Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.</p> 1:00 - Clinical knowledge in LLMs does not translate to human interactions 06:45 - From Tool to...

<p>In this episode, we’re lucky to be joined by Alexandre Sallinen and Tony O’Halloran from the Laboratory for Intelligent Global Health & Humanitarian Response Technologies to discuss how large language models are...

<p>Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.</p> 0:35 - Superhuman performance of a large language model on the reasoning tasks of a physician 06:20...

<p>We’re trying out a new episode format! We’ll be doing a quick wrap of the top three papers we found interesting over the last few weeks with some take home points.</p> 01:30 - Patient Reactions to Artificial...

<p>In this episode, we tackle some common myths about how generative AI works, why this is the case, implications for healthcare and some quick fixes. These myths include 1) that LLMs can explain their reasoning 2) that...

<p>In this episode, we discuss algorithmic bias and fairness in healthcare. We explain what this is, the different definitions of “fairness”, explore the ways in which bias can enter the machine learning pipeline and...

<p>We’ve returned after an accidental hiatus, just in time for the end of the year. In this episode, we’re joined by the team behind the American Medical Informatics Association (AMIA) Year in Review - Professor James...

<p >We’re back! This is the start of our regular discussions about healthcare AI topics and recent literature. On today’s episode - the 10 commandments of decision support, the checkered history of EMRs, clinicians as...

<p >In this episode, we discuss more of the technical aspects of LLM implementation in healthcare, including the following topics:</p> Embeddings Retrieval augmented generation (RAG) Fine tuning Low-Rank Adaptation...

<p >In this episode, we discuss some concerns about LLM implementation in the healthcare setting, including the following topics:</p> More detail about hallucinations, issues with accuracy Difficulties of model...

<p >Finally! We’re talking about large language models (LLMs) including ChatGPT. We discuss the following topics:</p> Brief explanation of transformer models and how they work including the attention mechanism and...