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AI and the Patient-Doctor Relationship asks a question that arrives earlier in medicine each year: what changes, and what should not, when artificial intelligence enters the space between a doctor and the person in front of them.
Written by a physician still in training, the book does not claim that AI will transform healthcare, nor that it threatens what makes medicine humane. Instead, it moves through the areas where AI is already present - diagnosis, monitoring, clinical decision support, mental health, and beyond - looking honestly at where the evidence for benefit is strong and where it is still developing, drawing on peer-reviewed research from journals including JAMA, NEJM, The Lancet, and Nature Medicine, alongside guidance from the WHO.
Throughout, the book returns to one distinction: the difference between recognizing a pattern and understanding a patient. That gap does not close simply because a tool improves, and much of the book is an attempt to describe, honestly, where it opens and where it can be narrowed.
It is written for clinicians, students, and anyone thinking through what AI is now asking of medicine - not as a technical guide, but as one doctor's attempt to work through the questions in the open.
AI and the Patient-Doctor Relationship asks a question that arrives earlier in medicine each year: what changes, and what should not, when artificial intelligence enters the space between a doctor and the person in front of them.
Written by a physician still in training, the book does not claim that AI will transform healthcare, nor that it threatens what makes medicine humane. Instead, it moves through the areas where AI is already present - diagnosis, monitoring, clinical decision support, mental health, and beyond - looking honestly at where the evidence for benefit is strong and where it is still developing, drawing on peer-reviewed research from journals including JAMA, NEJM, The Lancet, and Nature Medicine, alongside guidance from the WHO.
Throughout, the book returns to one distinction: the difference between recognizing a pattern and understanding a patient. That gap does not close simply because a tool improves, and much of the book is an attempt to describe, honestly, where it opens and where it can be narrowed.
It is written for clinicians, students, and anyone thinking through what AI is now asking of medicine - not as a technical guide, but as one doctor's attempt to work through the questions in the open.
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