Épisodes

  • In-context: January 5, 2026
    Jan 5 2026

    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

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    20 min
  • In-context: December 2, 2025
    Dec 2 2025

    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

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    23 min
  • In-context: November 3, 2025
    Nov 3 2025

    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

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    15 min
  • Should we be using LLMs for discharge summarisation?
    Oct 8 2025

    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

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    53 min
  • In-context: September 4, 2025
    Sep 4 2025

    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

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    20 min
  • In-context: August 18, 2025
    Aug 18 2025

    Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.

    • 00:30 - An Electrocardiogram Foundation Model Built on over 10 Million Recordings
    • 07:10 - Zero-shot Large Language Models for Long Clinical Text Summarization with Temporal Reasoning
    • 14:15 - Diagnostic Codes in AI prediction models and Label Leakage of Same-admission Clinical Outcomes
    • 16:50 - Evaluating reasoning LLMs’ potential to perpetuate racial and gender disease stereotypes in healthcare

    More details in the show notes on our website.

    Episodes | Bluesky | info@medicalattention.ai

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    19 min
  • In-context: July 20, 2025
    Jul 20 2025

    Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points.

    • 1:00 - Clinical knowledge in LLMs does not translate to human interactions
    • 06:45 - From Tool to Teammate: A Randomized Controlled Trial of Clinician-AI Collaborative Workflows for Diagnosis
    • 11:55 - Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study

    More details in the show notes on our website.

    Episodes | Bluesky | info@medicalattention.ai

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    20 min
  • Ep.10 Are benchmarks broken?
    Jun 21 2025

    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 assessed, including their Massive Open Online Validation & Evaluation (MOOVE) initiative.

    0:25 - Technical wrap: what are agents?

    13:20 - What are benchmarks?

    • 18:20 - Automated evaluation

    • 20:10 - Benchmarks

    • 37:45 - Human feedback

    • 44:50 - LLM as judge

    Read more about the projects we discuss here:

    • Meditron

    • Learn about the MOOVE or contact our team if you'd like to be involved
    • Listen to the LiGHTCAST including their recent excellent outline of the HealthBench paper

    More details in the show notes on our website.

    Episodes | Bluesky | info@medicalattention.ai

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    57 min