Medical Attention

Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
00:40 - Towards Conversational AI for Disease Management and Towards autonomous medical artificial intelligence agents
10:40 - Physicians and artificial intelligence diverge in evaluating large language models on real clinical cases
15:40 - Evaluating the robustness and readiness of large frontier models in health AI applications
Join the conversation on our new LinkedIn page: https://www.linkedin.com/company/medicalattention/
Episodes | Bluesky | info@medicalattention.ai

Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
00:30 - ChatGPT Health performance in a structured test of triage recommendations
11:30 - AI-Guided GDMT Optimization After HFrEF Hospitalization: The ASSIST-HF SIRIO Randomized Pilot Trial
18:25 - AI literacy mediates AI assisted diagnosis participation and critical thinking among medical students under supervision
Join the conversation on our new LinkedIn page: https://www.linkedin.com/company/medicalattention/
Episodes | Bluesky | info@medicalattention.ai

Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
01:00 - Technical wrap - ChatGPT and Claude for healthcare, AI scribes
07:40 - What is decision theory?
33:20 - Evaluation of performance measures in predictive artificial intelligence models to support medical decisions
Join the conversation on our new LinkedIn page: https://www.linkedin.com/company/medicalattention/
Episodes | Bluesky | info@medicalattention.ai

Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
00:30 - LLMs Can Do Medical Harm: Stress-Testing Clinical Decisions Under Social Pressure
09:30 - Measuring provider-level differences in perioperative workflow using computer vision-based artificial intelligence
12:55 - Heterogenous effect of automated alerts on mortality
Join the conversation on our new LinkedIn page: https://www.linkedin.com/company/medicalattention/
Episodes | Bluesky | info@medicalattention.ai

Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
00:30 - Ambient AI RCTs
A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being
Ambient AI Scribes in Clinical Practice: A Randomized Trial
AI Scribes Are Not Productivity Tools (Yet)
09:55 - Language models cannot reliably distinguish belief from knowledge and fact
17:20 - Extracting social determinants of health from electronic health records: development and comparison of rule-based and large language models-based methods
More details in the show notes on our website.
Episodes | Bluesky | info@medicalattention.ai

Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
00:35 - Scaling Large Language Models for Next-Generation Single-Cell Analysis
 
05:55 - Generative Medical Event Models Improve with Scale
 
10:50 - When helpfulness backfires: LLMs and the risk of false medical information due to sycophantic behavior
More details in the show notes on our website.
Episodes | Bluesky | info@medicalattention.ai

This episode, we discuss some of the challenges in using large language models (LLMs) for the task of summarising inpatient encounters. 
00:30 - Technical wrap - new models, MiT’s State of AI in Business 2025
12:40 - Medical summarisation
19:30 - Context Rot: How Increasing Input Tokens Impacts LLM Performance
30:50 - Verifiable Summarization of Electronic Health Records Using Large Language Models to Support Chart Review
40:00 - Evaluating large language models for drafting emergency department encounter summaries
42:25 - Evaluating Hospital Course Summarization by an Electronic Health Record-Based Large Language Model
More details in the show notes on our website.
Episodes | Bluesky | info@medicalattention.ai

Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.
00:30 - Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study
 
06:05 - Automation Bias in Large Language Model Assisted Diagnostic Reasoning Among AI-Trained Physicians
 
10:15 - Emerging algorithmic bias: fairness drift as the next dimension of model maintenance and sustainability 
 
15:20 - Evaluating Large Language Model Diagnostic Performance on JAMA Clinical Challenges via a Multi-Agent Conversational Framework
More details in the show notes on our website.
Episodes | Bluesky | info@medicalattention.ai