Medical Attention

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.

• 01:30 - Patient Reactions to Artificial Intelligence-Clinician Discrepancies
• 06:50 - AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans for mortality prediction 
• 11:10 - Large-scale Local Deployment of DeepSeek-R1 in Pi...

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 LLMs can express uncertainty, 3) that LLMs can a) do maths, b) manage temporal data c) apply guidelines d) handle negation and finally that 4) that AI will replace clinicians.

02:00 Technical update - DeepSeek, other n...

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 Cimino, Pushkala Jayaraman and Dr Humayera Islam to talk about the main themes in healthcare AI for 2024.

01:00 Technical update (ChatGPT-o1, agentic AI) 10:25 AMIA Year in Review

Episodes | Bluesky | info@medicalattenti...

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 “moral crumple zone” for AI models and much more.

01:18 Technical update (Llama 3.1, Phi releases)

06:25 Main discussion

41:20 Article round-up

Episod...

In this episode, we discuss more of the technical aspects of LLM implementation in healthcare, including the following topics:

• Embeddings
• Retrieval augmented generation (RAG)
• Fine tuning
• Low-Rank Adaptation (LoRA)
• Small models
• Quantisation
• Encoder and decoder models
• Multimodal...

In this episode, we discuss some concerns about LLM implementation in the healthcare setting, including the following topics:

• More detail about hallucinations, issues with accuracy 
• Difficulties of model evaluation
• Concerns regarding bias and equity
• Governance and monitoring of LLMs in a healthcare settings

Episodes | Twitter | inf...

Finally! We’re talking about large language models (LLMs) including ChatGPT. We discuss the following topics:

• Brief explanation of transformer models and how they work including the attention mechanism and context window
• Discuss a brief development of LLMs to this point
• How LLMs are trained
• Some limitations - privacy, accuracy, provenance
...

In this episodes we give an overview of neural networks and how they’re used in healthcare. We'll be covering the following topics:

• Definition of neural networks and a high level explanation of their structure
• Overview of the development of neural networks and use in healthcare
• How neural networks are currently used in medicine
• Limitations...