Titlebook: Digital Mental Health; A Practitioner‘s Gui Ives Cavalcante Passos,Francisco Diego Rabelo-da-P Book 2023 The Editor(s) (if applicable) and

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Prediction of Suicide Risk Using Machine Learning and Big Data,ment of suicide risk remains largely subjective, highlighting the urgent need for more objective and precise tools to predict suicide risk at an individual level. Considering this, big data and machine learning models provide an opportunity to facilitate the early implementation of preventive and tr

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Electronic Health Records to Detect Psychosis Risk, health records (EHRs) contain detailed individual-level data that are routinely collected as part of clinical care, providing a unique opportunity for personalised prognostication. This chapter explores current detection strategies, their limitations and how prognostic models leveraging EHR data ha

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The Use of Artificial Intelligence to Identify Trajectories of Severe Mental Disorders,tive and psychosocial impairments. They are also highly heterogeneous with regard to clinical courses. Machine learning algorithms can identify subtle factors related to different trajectories, enabling them to predict the probability of a specific outcome at the individual level or even to identify

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Robert Morrison,Daniel Sanjiv Robertsings are discussed, including gains related to increasing access to mental health care, facilitating data collection and management, and promoting patient disclosure. Possible concerns about the use of chatbots are also discussed, highlighting the importance of accounting for patient safety, privacy

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