Algorithms & Adipose

Algorithms & Adipose

By Farah Deshmukh MD MPHTechnology
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Algorithms & Adipose episodes

  • Episode 7: Three Ways to Make AI 'Medical'

    In this episode we talk about the three ways to make AI "medical", fine-tuning, retrieval, and prompting, what each one actually does, and how to tell them apart when a vendor is selling to you. Plus why a general model, prompted well, beat the specialized medical one.
    Paper: Nori H, et al. Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine. arXiv:2311.16452. 2023.
    Substack: https://algoadipose.substack.com
    Music credit: NCS Dream – Di Young


    16 min
  • Episode 6: Training vs. Using

    In this episode we talk about training vs. using - how these models are built, why they have a knowledge cutoff, and why they never actually learn from your corrections no matter how many times you correct them.
    Paper: Singhal K, et al. Large language models encode clinical knowledge. Nature. 2023;620(7972):172-180.
    Substack: https://algoadipose.substack.com
    Music credit: NCS Dream – Di Young

    22 min
  • Episode 5: How You Ask Changes What You Get

    This episode: Why a prompt isn't a request but a set of conditions, why "be accurate" accomplishes nothing, and why letting a model say "I don't know" is the highest-leverage move you can make.Paper: Pandit S, et al. MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in LLMs. EMNLP 2025.

    Substack: https://algoadipose.substack.com

    Music credit: NCS Dream – Di Young


    18 min
  • Episode 4: What is RAG?

    This episode: retrieval-augmented generation - giving the model a library instead of a memory.


    Paper: Zakka C, et al. Almanac — Retrieval-Augmented Language Models for Clinical Medicine. NEJM AI. 2024;1(2).

    Substack: https://algoadipose.substack.com

    Music credit: NCS Dream – Di Young




    17 min
  • Episode 3: Why It Makes Things Up

    This episode: hallucination. The model produces a correct answer and a completely fabricated one by exactly the same process.

    Paper: Pal A, et al. Med-HALT: Medical Domain Hallucination Test for Large Language Models. CoNLL 2023.

    Substack: https://algoadipose.substack.com

    Music credit: NCS Dream – Di Young


    18 min
  • Episode 2: Tokens and Context

    In this episode we talk about tokens and context - the model's working memory. What's in it, what falls out, why long chats degrade, and why a bigger context window is not the same as a bigger attention span.

    Paper: Liu NF, et al. Lost in the Middle: How Language Models Use Long Contexts. TACL. 2024;12:157-173.

    Substack: https://algoadipose.substack.com

    Music credit: NCS Dream – Di Young


    17 min
  • Episode 1: "The Prediction Machine"

    what actually happens in the seconds after you hit enter after typing your prompt.

    Paper: Goh E, et al. Large Language Model Influence on Diagnostic Reasoning: A Randomized Clinical Trial. JAMA Netw Open. 2024;7(10):e2440969.

    Substack: https://algoadipose.substack.com

    Music credit: NCS Dream – Di Young


    16 min

About Algorithms & Adipose

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A practical, evidence-based show for physicians who want to understand AI in Medicine.