Additional information
by Mariam Khayretdinova (Author)
A critical introduction to the psychiatric technologies of the future
Artificial intelligence (AI) promises to transform nearly every area of modern life, and psychiatry is no exception. The field faces the mounting crisises in diagnostic inaccuracy, treatment stagnation, and persistent failures in suicide prevention, while traditional approaches struggle to keep pace with patient needs. AI and neuroscience offer a new path forward, pointing toward a future where mental health care is grounded in objective data, individualized predictions, and biologically informed treatments.
Decoding Despair provides a cutting-edge look at these emerging scientific possibilities and the long-standing norms they may replace. Beginning with an examination of psychiatry's current challenges, it moves toward a present where AI-powered tools are beginning to reshape diagnostics, treatment selection, and drug development. The book offers readers a deeper understanding of mental health as both a scientific field and a lived human experience, while igniting an essential conversation about the transformative potential of precision psychiatry and technology.
Decoding Despair readers will also find:
- Exploration of the patient's journey from first symptoms to being prescribed medication
- Deep dive into the healthcare system and an understanding of the connections between stakeholders
- Clear explanations of how AI models work and how they can be practically applied to solving issues in mental health
- Deep introduction into the world of data and the different models of data acquisition necessary for building AI solutions
- Analysis of the potential innovations that could come first and the conditions necessary for them to occur
Decoding Despair is ideal for professionals and innovators building the future of psychiatry--as well as anyone seeking to understand their own mental health and the technological breakthroughs poised to reshape this critical field of care.
Front Jacket
In Decoding Despair: How AI is Reshaping Psychiatry, veteran researcher and brain-science entrepreneur Mariam Khayretdinova delivers a singularly insightful exploration of how artificial intelligence and data science are transforming mental health care. The book confronts the pressing challenges facing psychiatry today--including the development of accurate diagnostics, the implementation of effective treatments and drug discovery, and suicide prevention--while charting a clear path toward solving them through AI-driven innovation.
Khayretdinova guides readers through a comprehensive three-part journey. First, she examines the psychiatric system from both the patient's perspective and the system itself, identifying the root problems plaguing the field. Second, she provides an accessible introduction to artificial intelligence, explaining the mechanisms behind current AI models, their potential and limitations, and the types of data required to build effective mental health tools. Finally, she demonstrates how AI can be practically applied to revolutionize diagnostics, predict treatment response, accelerate drug discovery, and prevent suicide.
Decoding Despair offers a clear-eyed view of the psychiatric field as an interconnected system of stakeholders--patients, clinicians, and pharmaceutical companies--each facing distinct but related challenges. The author examines the complexities of drug development, the biological obstacles that cause promising treatments to fail despite major investments, and the critical role that data plays in understanding mental disorders. She then reveals how emerging technologies are expected to enter the market and what conditions are necessary to make precision psychiatry accessible to those who need it most.
Perfect for professionals and innovators developing new solutions in psychiatry and mental health--particularly those working on diagnostics, treatment optimization, drug discovery, and digital technologies--Decoding Despair is also a must-read for everyone interested in solving longstanding problems in psychiatry with artificial intelligence.
Back Jacket
An instruction manual for using AI to solve some of the hardest problems in psychiatry
Psychiatry faces critical obstacles that have resisted solution for decades: inaccurate diagnostics, ineffective treatment implementation, and inadequate suicide prevention. In Decoding Despair: How AI is Reshaping Psychiatry, veteran researcher and brain-science entrepreneur Mariam Khayretdinova charts a clear path toward solving these problems with artificial intelligence.
Khayretdinova guides readers through psychiatry's interconnected ecosystem of patients, clinicians, and pharmaceutical companies, revealing why promising treatments fail despite major investments and exposing the biological obstacles that stand in the way. She provides an accessible introduction to artificial intelligence--its mechanisms, current models, capabilities, and limitations--specifically tailored for mental health applications.
The book demonstrates how emerging AI technologies can revolutionize diagnostics, predict individual treatment responses, accelerate drug discovery, and prevent suicide. Khayretdinova examines the data requirements, funding realities, and market conditions necessary to make precision psychiatry accessible to those who need it most.
Decoding Despair is essential reading for professionals and innovators developing new solutions in psychiatry and mental health--particularly those focused on diagnostics, treatment optimization, drug discovery, and digital technologies. It's also a must-read for anyone committed to solving psychiatry's longstanding challenges through AI.
Author Biography
Mariam Khayretdinova is CEO and Co-founder of Brainify.AI, a New York City-based neurotech start-up which specializes in using AI and machine learning to analyze brain wave activity and create personalized psychiatric care based on individual biological profiles. She holds two Master's degrees, one in Applied Mathematics and another in Psychology from Harvard University and is currently continuing her research at the University of Cambridge, Department of Applied Mathematics and Theoretical Physics.
