Abstract
Computers are capable of learning how to solve complex problems. The emergence of machine learning (ML) represents a major advance for the field of mental health. ML algorithms can be trained to recognize subgroups of people with similar symptoms (diagnosis), to estimate the probability of recovery from these symptoms (prognosis), to make a judgment about the best treatment option for a patient (treatment selection), and even to provide feedback and guidance to therapists by learning from recordings of effective therapist-patient interactions (process feedback). This article offers an introduction to ML and the emerging field of precision mental health care.
| Original language | English |
|---|---|
| Title of host publication | Encyclopedia of Mental Health, Third Edition |
| Subtitle of host publication | Volume 1-3 |
| Publisher | Elsevier |
| Pages | V1-132-V1-142 |
| Volume | 1 |
| ISBN (Electronic) | 9780323914987 |
| ISBN (Print) | 9780323914970 |
| DOIs | |
| State | Published - 1 Jan 2023 |
Bibliographical note
Publisher Copyright:© 2023 Elsevier Inc. All rights reserved.
Keywords
- AI
- Artificial intelligence
- Clinical prediction models
- Data mining
- Data science
- Deep learning
- Machine learning
- Natural language processing
- Precision medicine
- Precision mental health care
- Statistical learning
