The Psychology of Health

Chatbots and large language models are becoming increasingly common in everyday life, but their growing presence in healthcare has raised an important question: Should probabilistic AI systems be used to help make medical decisions? This episode takes a clear, grounded look at why the answer is far more complicated—and potentially far more dangerous—than many people realize.

Modern chatbots work by predicting the most statistically ...

Another week, another headline declaring AI has officially surpassed physicians. This time, it's a study published in Science on April 30, 2026, claiming that OpenAI's o1 model "outperformed physician baselines" across multiple diagnostic reasoning tasks. The research comes from Harvard, Stanford, and Beth Israel Deaconess Medical Center. It's rigorous. It's peer-reviewed. And it's already being cited ...

Artificial intelligence is rapidly moving into classrooms, clinics, and daily healthcare decision making, but much of the public conversation is built on a dangerous misunderstanding. Too often, people now treat artificial intelligence as if it simply means chatbots. In this episode, Dr. Milan Toma explains why that confusion matters and why healthcare professionals must learn to distinguish between conversational tools and task sp...

Introduction: A Tale of Two Rounds

Every attending physician has seen the "Star Student" who can quote the New England Journal of Medicine verbatim but freezes when a patient doesn't follow the script. In this episode, we introduce Student A and Student B.

• Student A (The Memorizer): They have a mental database of every practice vignette. They are fast, confident, and statistically "perfect" on paper.

• Studen...

Have you ever wondered why skepticism about artificial intelligence persists in healthcare, even as new AI tools are rapidly introduced? In this episode, Dr. Milan Toma, Associate Professor of Clinical Sciences at NYIT College of Osteopathic Medicine, explains the roots of distrust in clinical AI systems and what it takes to regain confidence. Drawing on decades of machine learning evolution, real-world case studies, and his own re...

Imagine you are developing an AI system to predict which patients are at risk of becoming obese based on their lifestyle factors. You gather data on diet, exercise habits, sleep patterns, stress levels, and dozens of other variables. You train your model. It achieves 99% accuracy. You celebrate.Then someone points out that you included the patients' current weight in your dataset.Your model did not learn anything about lifestyl...

When a ninety nine percent accurate AI misses every single case of disease, something has gone terribly wrong.

In this episode, Dr. Milan Toma exposes one of the most dangerous pitfalls in medical artificial intelligence: the accuracy paradox. Discover why impressive accuracy numbers can mask complete clinical failure, and why that four percent drop in accuracy might actually save lives.

Dr. Toma explains how the fundamental nature o...

What can a 2017 colonoscopy study teach us about using AI diagnostics safely in 2025?

An AI diagnostic tool boasts 99% accuracy. Should you trust it? In this episode, I explain why that number can be dangerously misleading and equip medical professionals with the practical strategies needed to see through the hype and protect their patients.As artificial intelligence becomes more integrated into healthcare, the ability to critic...

Are we caught in another tech hype cycle with AI? The promise of technology often clashes with financial and practical reality. This presentation cuts through the noise to offer a clear and balanced framework for thinking about the future of artificial intelligence in business and society.Join me for a thoughtful exploration of how to navigate the booms and busts of innovation. Using the "Could, Should, Might, and Don't&qu...

This episode provides an overview of Total Energy Expenditure (TEE) and Basal Energy Expenditure (BEE), emphasizing their definitions, measurement methods, and patterns across the human lifespan. It explains that TEE is the total of all calories burned, comprised mainly of BEE (the energy needed for basic functions at rest), the Thermic Effect of Food, and Physical Activity Energy Expenditure. Contrary to common beliefs, I explain ...

This episode challenges the common belief that weight gain in middle age is caused by a slowing metabolism, asserting that adult metabolism generally remains stable until after age sixty. Instead, it explains that weight gain is primarily driven by lifestyle factors, such as reduced physical activity and increased caloric intake. It details how the body mounts a powerful biological defense against weight loss, interpreting caloric ...

This episode fundamentally challenges the popular belief that human metabolism slows down during midlife, asserting instead that total energy expenditure remains stable between the ages of 20 and 60, only declining after age 60. Using gold-standard measurements, the text explains that the weight gain many adults experience is not due to a slowing metabolism but rather to changes in body composition, specifically the loss of lean mu...

This episode provides an overview of the significant challenge of dietary underreporting bias in nutrition research, especially concerning individuals with obesity. It explains how some people with higher body mass index (BMI) systematically and substantially under-report their true food and calorie consumption, often by 700 to 850 kcal per day, which is far more than their lean counterparts. The episode highlights that doubly labe...

This episode provides an extensive critique of the reliability of self-reported dietary surveillance data, arguing that simple correlations between dietary trends (like increased calories or changes in macronutrients) and the rise in U.S. obesity rates are misleading. The episode emphasizes that correlation does not equal causation and highlights the significant problem of systematic underreporting of calorie intake, particularly a...

This episode provides an extensive overview of the complex biological regulation of appetite and energy balance, moving beyond the simple "calories in, calories out" model. It establishes that fat tissue is an active endocrine organ that produces hormones crucial for signaling the brain about the body's energy status. The episode highlights the central role of the hormone leptin, explaining that it suppresses hunger w...

This episode provides an extensive overview of the strong relationship between insufficient sleep and the increased risk of weight gain and metabolic dysfunction. It emphasizes that epidemiological data consistently identify short sleep duration as an independent risk factor for obesity, particularly in younger populations. Mechanistically, sleep deprivation is shown to disrupt appetite-regulating hormones, specifically by decreasi...