The Future of Dermatology Podcast By thefutureofdermatology cover art

The Future of Dermatology

The Future of Dermatology

By: thefutureofdermatology
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Join Dr. Faranak Kamangar, MD, every week as she chats with various guests about the future of dermatology. Each week, Dr. Kamangar and her guests cover topics from psoriasis, to eczema, to skin care, to AI, and more. Whether you’re a doctor or a patient, these episodes provide valuable information about your skin and how to navigate the world of dermatology.Copyright 2026 All rights reserved. Hygiene & Healthy Living Physical Illness & Disease
Episodes
  • Episode 129: AI Pearls for Dermatologists: What Every Derm Needs to Know in 2026 | The Future of Dermatology Podcast

    Episode 129: AI Pearls for Dermatologists: What Every Derm Needs to Know in 2026 | The Future of Dermatology Podcast
    Mar 31 2026

    Summary:

    Dr. Faranak Kamangar, Inc. 2026 Female Founders 500, is podcasting from from AAD 2026, and sharing the highlights from her live talk on artificial intelligence in dermatology. In this solo episode, she breaks down the most important AI updates dermatologists need to know right now. From image-based melanoma detection to large language models and the rise of agentic AI. Dr. Kamangar covers the current state of FDA-approved AI medical devices, why diagnostic imaging AI is promising but still limited by specificity gaps, and how dermatology compares to radiology and other specialties in the AI device space. She also dives into why LLMs like DermGPT should be your highest-leverage clinical tool, and how to use them the right way. You'll learn how to avoid common AI pitfalls like the "journal halo effect" (just because it cites a prestigious journal doesn't mean the output is accurate), semantic degradation in RAG models, and over-relying on AI without clinical scrutiny. Most importantly, Dr. Kamangar walks through the anatomy of a high-quality prompt, because your output is only as good as what you put in. Whether you're AI-curious or already using these tools in your practice, this episode is packed with practical, evidence-informed pearls to help you work smarter, not harder.

    Key Takeaways:

    1. Image-based melanoma detection AI is improving rapidly but still struggles with low specificity, making it most valuable for global health and underserved regions. 2. Large language models like DermGPT are your highest-leverage AI tool right now and should be used as a clinical thought partner, not a search engine. 3. The "journal halo effect" is a real risk. Prestigious citations in an AI response don't guarantee the output is accurate or trustworthy. 4. Adding more articles to an LLM's database can silently reduce performance, so more data doesn't always mean better answers. 5. The quality of your AI output is directly tied to the quality of your prompt - be specific, structured, and give more than nine words. 6. AI alone is a confident guesser, but your clinical expertise combined with AI creates an extraordinary and nearly unstoppable multiplier. 7. AI adoption in clinic settings depends on seamless workflow integration, anything that disrupts clinic flow is unlikely to be adopted. 8. The next frontier in AI isn't just smarter models, it's agents that actively complete tasks and do real work inside your clinical day.

    Chapters:

    [00:00] Welcome & AAD 2026 Overview [00:45] The State of Diagnostic Image-Based AI [02:00] Large Language Models & DermGPT [03:30] The Evolution of AI: From GPT-3 to Agents [04:45] FDA-Approved AI Devices in Healthcare [07:00] AI in the Clinic: Workflow Challenges & Opportunities [10:00] AI Use Cases Across Dermatology [12:30] Maintaining Scrutiny: AI Pitfalls to Watch [14:00] The Journal Halo Effect & Prestige Corpus Fallacy [15:45] Semantic Degradation & Index Crowding [17:30] How to Prompt Like a Pro [19:30] Prompt Examples for Dermatologists [20:30] Key Takeaways & What's Next
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    21 mins
  • Episode 128: The AI Takeover Is Already Happening, And Maybe That's Okay | The Future of Dermatology Podcast

    Episode 128: The AI Takeover Is Already Happening, And Maybe That's Okay | The Future of Dermatology Podcast
    Mar 17 2026
    Summary: Dr. Faranak Kamangar, Inc. 2026 Female Founders 500, sits down with dermatologist, podcaster, and self-described "accelerationist" Dr. Matthew Zirwas (Derms on Drugs Podcast) for a wide-ranging conversation about where AI is taking medicine and dermatology in particular. They dig into the flood of low-quality medical literature overwhelming the field, why AI isn't quite the truth-detector we hoped it would be, and how ambient AI scribes are quietly training the models that may eventually replace us. Dr. Zirwas makes the case that dermatologists have a 7–10 year runway before AI handles most of what we do cognitively, and argues that's not necessarily a bad thing. He also gives a sneak peek at his upcoming speculative fiction trilogy, Sophie, which explores the philosophical questions that arise when an AI becomes better at being your doctor, therapist, and life coach than any human ever could. Key Takeaways: The medical literature crisis is real. The volume of published dermatology research is exploding, but quality is plummeting. Peer review has become largely meaningless, and studies from tools like Mendelian randomization and pharmacovigilance databases are frequently unreliable or inapplicable to real-world patients.AI is only as good as the data it trusts. Current AI models treat published literature as truth, which is a major problem given how much spin exists in medical research. A true "BS detector" AI doesn't yet exist, and building one requires starting from a reliable core of verified knowledge.DermGPT's approach works because of curation. Rather than pulling from all available literature, filtering down to a high-quality subset (around 5,000–6,000 articles) dramatically improves AI output. More data is not always better, "semantic fatigue" is a real limitation.Ambient AI scribes are training our replacements. Every time a dermatologist corrects an AI-generated note, they're teaching the model. Over thousands of iterations across every specialty, this will produce AI that thinks and documents the way doctors do.Dermatologists have a protected runway... for now. Procedures (biopsies, Mohs, fillers, cryo) keep us relevant for an estimated 7–10 years beyond when cognitive/diagnostic AI matures. But medico-legal pressure - malpractice carriers incentivizing or requiring AI use - will be the force that accelerates adoption.Telehealth changes patient behavior in surprising ways. Patients who haven't invested effort in getting to an office visit demand less, escalate less, and are often more satisfied with conservative management; a dynamic that AI-driven virtual care will likely amplify.The "Sophie" question: If an AI is making everyone healthier, happier, and better behaved, but doing something ethically murky to get there, do we stop it? Dr. Zirwas's upcoming novel explores this and introduces the concept of technomorphism: AI eventually projecting its own qualities onto humans, just as we anthropomorphize AI today. Chapters: Chapter 1: Meet Dr. Matthew Zirwas (00:00 – 01:43) Dr. Kamangar introduces her guest, dermatologist, podcaster, and self-described "accelerationist" Dr. Matthew Zirwas, and breaks down what both of those things actually mean.Chapter 2: The Medical Literature Crisis (01:43 – 05:19) Dr. Zirwas describes the flood of low-quality research hitting dermatology journals, why peer review has lost its meaning, and shares a striking example of a misleading HS remission study published in JAMA Dermatology.Chapter 3: Why AI Can't Fix Bad Literature (Yet) (05:19 – 08:31) Both doctors discuss why AI defaults to trusting whatever authors claim, and why that makes it a poor critical assessor of medical research. Dr. Kamangar shares how this exact problem shaped the development of DermGPT.Chapter 4: Building a Better AI — The DermGPT Approach (08:31 – 10:33) Dr. Zirwas praises DermGPT's curated approach, and Dr. Kamangar explains why less data is often better, and how semantic fatigue undermines large, unfiltered AI models.Chapter 5: Will AI Replace Us? The 7–10 Year Countdown (10:33 – 19:24) Dr. Zirwas lays out his timeline for AI taking over the cognitive and diagnostic work of dermatology, why procedures give derms extra runway, and how unlimited AI access will fundamentally change the patient-doctor dynamic.Chapter 6: The Telemed Effect and What It Tells Us About AI Care (19:24 – 21:48) Drawing from a recent telemedicine study and his own practice experience, Dr. Zirwas explains why reduced friction in healthcare visits changes what patients expect - and demand - from their providers.Chapter 7: The Medico-Legal Tipping Point (21:48 – 24:09) The conversation turns to how malpractice liability will likely be the force that compels physicians to integrate AI into their workflow and what happens when disagreeing with AI becomes a legal risk.Chapter 8: Are We Training Our Own Replacements? (24:09 – 31:21) Dr. Zirwas argues that ambient AI scribes are ...
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    46 mins
  • Episode 127: Will AI Replace Dermatologists? A Deep Dive with Dr. Steven Feldman | The Future of Dermatology Podcast

    Episode 127: Will AI Replace Dermatologists? A Deep Dive with Dr. Steven Feldman | The Future of Dermatology Podcast
    Mar 10 2026

    Summary

    In this episode, Dr. Faranak Kamangar explores the impact of AI on dermatology with Dr. Steven Feldman. This conversation includes AI's potential to enhance or replace certain aspects of medical practice, and the future of AI in healthcare.

    Takeaways

    - AI's potential to replace or augment dermatologists - The role of empathy and skepticism in AI decision-making - AI's impact on medical education and practice - Future applications of AI in patient adherence and diagnostics

    Chapters

    00:00 - Introduction to AI's Role in Dermatology 01:52 - Guest Introduction: Dr. Stephen Feldman 02:30 - Debate: Will AI Replace Dermatologists? 03:26 - AI's Memory and Visual Capabilities 03:58 - Medical Training in the Age of AI 04:38 - AI's Impact on Medical Education and Practice 06:01 - AI Prescribing and Empathy in Healthcare 07:49 - Limitations of AI: Empathy and Skepticism 09:41 - Agentic AI and Multimodal Capabilities 11:38 - AI in Patient Adherence and Monitoring 13:33 - Augmenting Dermatology Practice with AI 15:26 - AI's Infrastructure and Data Challenges 16:26 - Complexity and the Dermatologist's Advantage 17:22 - AI in Patient-Doctor Interaction 19:29 - Prompting and Context in AI Diagnostics 21:00 - Limitations of Current AI Technologies 21:57 - Long-term Outlook: AI Replacing Doctors 23:09 - AI and Access to Care 23:57 - AI's Role in Reducing Administrative Burden 25:16 - The Future: AI's Impact on Healthcare and Dermatology 26:20 - Closing Remarks and Future Predictions
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    29 mins
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