Artificial Intelligence for Mental Healthcare: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom

Characterizing the role of dermatologists in developing artificial intelligence for assessment of skin cancer: A systematic review

(2020) George A. Zakhem et al.   JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY

Battling the Modern Behavioral Epidemic of Loneliness

(2020) Dilip V. Jeste et al.   JAMA Psychiatry

Predicting treatment dropout after antidepressant initiation

(2020) Melanie F. Pradier et al.   Translational Psychiatry

Artificial intelligence in health care: accountability and safety

(2020) Ibrahim Habli et al.   BULLETIN OF THE WORLD HEALTH ORGANIZATION

eXplainable Artificial Intelligence (XAI) for the identification of biologically relevant gene expression patterns in longitudinal human studies, insights from obesity research

(2020) Augusto Anguita-Ruiz et al.   PLoS Computational Biology

Latent bias and the implementation of artificial intelligence in medicine

(2020) Matthew DeCamp et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

Explainable artificial intelligence model to predict acute critical illness from electronic health records

(2020) Simon Meyer Lauritsen et al.   Nature Communications

Expanding technology for engagement in dementia while ensuring equity, interoperability, and privacy

(2020) Danny W. Linggonegoro et al.   INTERNATIONAL PSYCHOGERIATRICS

Applied natural language processing in mental health big data

(2020) Robert Stewart et al.   NEUROPSYCHOPHARMACOLOGY

Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets

(2020) Marc-Andre Schulz et al.   Nature Communications

Levels of Severity of Depressive Symptoms Among At-Risk Groups in the UK During the COVID-19 Pandemic

(2020) Eleonora Iob et al.   JAMA Network Open

A Comprehensive Survey on Transfer Learning

(2020) Fuzhen Zhuang et al.   PROCEEDINGS OF THE IEEE

Patient Feedback on the Use of Predictive Analytics for Suicide Prevention

(2020) Mark A. Reger et al.   PSYCHIATRIC SERVICES

The Challenges and Opportunities of Small Effects

(2019) Martin P. Paulus et al.   JAMA Psychiatry

Deep neural networks in psychiatry

(2019) Daniel Durstewitz et al.   MOLECULAR PSYCHIATRY

A deep transfer learning approach for improved post-traumatic stress disorder diagnosis

(2019) Debrup Banerjee et al.   KNOWLEDGE AND INFORMATION SYSTEMS

Research Domain Criteria scores estimated through natural language processing are associated with risk for suicide and accidental death

(2019) Thomas H. McCoy et al.   DEPRESSION AND ANXIETY

Study of Independent Living Residents of a Continuing Care Senior Housing Community: Sociodemographic and Clinical Associations of Cognitive, Physical, and Mental Health

(2019) Dilip V. Jeste et al.   AMERICAN JOURNAL OF GERIATRIC PSYCHIATRY

Speech‐based markers for posttraumatic stress disorder in US veterans

(2019) Charles R. Marmar et al.   DEPRESSION AND ANXIETY

Exploration, Inference, and Prediction in Neuroscience and Biomedicine

(2019) Danilo Bzdok et al.   TRENDS IN NEUROSCIENCES

Alcoholism Identification Based on an AlexNet Transfer Learning Model

(2019) Shui-Hua Wang et al.   Frontiers in Psychiatry

Building the case for actionable ethics in digital health research supported by artificial intelligence

(2019) Camille Nebeker et al.   BMC Medicine

Leveraging Digital Health and Machine Learning Toward Reducing Suicide—From Panacea to Practical Tool

(2019) John Torous et al.   JAMA Psychiatry

Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data

(2019) Afsaneh Doryab et al.   JMIR mHealth and uHealth

Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry

(2019) Andy M.Y. Tai et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force

(2019) Ives C. Passos et al.   BIPOLAR DISORDERS

Do no harm: a roadmap for responsible machine learning for health care

(2019) Jenna Wiens et al.   NATURE MEDICINE

Key challenges for delivering clinical impact with artificial intelligence

(2019) Christopher J. Kelly et al.   BMC Medicine

How to Read Articles That Use Machine Learning

(2019) Yun Liu et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics

(2019) Tong He et al.   NEUROIMAGE

Artificial intelligence and the future of psychiatry: Insights from a global physician survey

(2019) P. Murali Doraiswamy et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research

(2019) Young Juhn et al.   JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review

(2019) Sarah A. Graham et al.   PSYCHIATRY RESEARCH

Machine Learning Approaches for Clinical Psychology and Psychiatry

(2018) Dominic B. Dwyer et al.   Annual Review of Clinical Psychology

Meeting Report: Can We Make Animal Models of Human Mental Illness?

(2018) Lisa M. Monteggia et al.   BIOLOGICAL PSYCHIATRY

Points of Significance: Statistics versus machine learning

(2018) Danilo Bzdok et al.   NATURE METHODS

From Maps to Multi-dimensional Network Mechanisms of Mental Disorders

(2018) Urs Braun et al.   NEURON

Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction

(2018) Seong Ho Park et al.   RADIOLOGY

Bridging the dichotomy of actual versus aspirational digital health

(2018) John Torous et al.   World Psychiatry

Prediction of psychosis across protocols and risk cohorts using automated language analysis

(2018) Cheryl M. Corcoran et al.   World Psychiatry

Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps

(2018) John Torous et al.   Current Psychiatry Reports

Mental health monitoring with multimodal sensing and machine learning: A survey

(2018) Enrique Garcia-Ceja et al.   Pervasive and Mobile Computing

Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data

(2018) Milena A. Gianfrancesco et al.   JAMA Internal Medicine

Ensuring Fairness in Machine Learning to Advance Health Equity

(2018) Alvin Rajkomar et al.   ANNALS OF INTERNAL MEDICINE

Questions for Artificial Intelligence in Health Care

(2018) Thomas M. Maddox et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Integrating Predictive Modeling Into Mental Health Care: An Example in Suicide Prevention

(2018) Greg M. Reger et al.   PSYCHIATRIC SERVICES

The Science of Prognosis in Psychiatry

(2018) Paolo Fusar-Poli et al.   JAMA Psychiatry

Advances in Social Media Research: Past, Present and Future

(2017) Kawaljeet Kaur Kapoor et al.   INFORMATION SYSTEMS FRONTIERS

Erratum: Resting-state connectivity biomarkers define neurophysiological subtypes of depression

(2017) Andrew T Drysdale et al.   NATURE MEDICINE

Inference in the age of big data: Future perspectives on neuroscience

(2017) Danilo Bzdok et al.   NEUROIMAGE

Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications

(2017) Sandra Vieira et al.   NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

Web-based Social Media Intervention to Increase Vaccine Acceptance: A Randomized Controlled Trial

(2017) Jason M. Glanz et al.   PEDIATRICS

Reevaluating the Efficacy and Predictability of Antidepressant Treatments

(2017) Adam M. Chekroud et al.   JAMA Psychiatry

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers

(2016) Brett A. Clementz et al.   AMERICAN JOURNAL OF PSYCHIATRY

Individualized identification of euthymic bipolar disorder using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and machine learning

(2016) Mon-Ju Wu et al.   JOURNAL OF AFFECTIVE DISORDERS

Structural brain changes are associated with response of negative symptoms to prefrontal repetitive transcranial magnetic stimulation in patients with schizophrenia

(2016) A Hasan et al.   MOLECULAR PSYCHIATRY

Predicting early psychiatric readmission with natural language processing of narrative discharge summaries

(2016) A Rumshisky et al.   Translational Psychiatry

Uncovering the Hidden Risk Architecture of the Schizophrenias: Confirmation in Three Independent Genome-Wide Association Studies

(2015) Javier Arnedo et al.   AMERICAN JOURNAL OF PSYCHIATRY

Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition Study

(2015) Lianne Schmaal et al.   BIOLOGICAL PSYCHIATRY

Role of social media and the Internet in pathways to care for adolescents and young adults with psychotic disorders and non-psychotic mood disorders

(2015) Michael L. Birnbaum et al.   Early Intervention in Psychiatry

Brain Imaging During the Transition from Psychosis Prodrome to Schizophrenia

(2015) Yoonho Chung et al.   JOURNAL OF NERVOUS AND MENTAL DISEASE

Stratifying Risk for Renal Insufficiency Among Lithium-Treated Patients: An Electronic Health Record Study

(2015) Victor M Castro et al.   NEUROPSYCHOPHARMACOLOGY

The role of machine learning in neuroimaging for drug discovery and development

(2015) Orla M. Doyle et al.   PSYCHOPHARMACOLOGY

Brain disorders? Precisely

(2015) T. R. Insel et al.   SCIENCE

Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

(2014) Truyen Tran et al.   BMC Psychiatry

Neuropsychosocial profiles of current and future adolescent alcohol misusers

(2014) Robert Whelan et al.   NATURE

A Cognitive–Emotional Biomarker for Predicting Remission with Antidepressant Medications: A Report from the iSPOT-D Trial

(2014) Amit Etkin et al.   NEUROPSYCHOPHARMACOLOGY

Brain Morphometric Biomarkers Distinguishing Unipolar and Bipolar Depression

(2014) Ronny Redlich et al.   JAMA Psychiatry

Blood-based gene-expression predictors of PTSD risk and resilience among deployed marines: A pilot study

(2013) Stephen J. Glatt et al.   AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS

A machine learning approach using EEG data to predict response to SSRI treatment for major depressive disorder

(2013) Ahmad Khodayari-Rostamabad et al.   CLINICAL NEUROPHYSIOLOGY

Single-Subject Anxiety Treatment Outcome Prediction using Functional Neuroimaging

(2013) Tali M Ball et al.   NEUROPSYCHOPHARMACOLOGY

Electroencephalography-Derived Biomarkers of Antidepressant Response

(2011) Dan Vlad Iosifescu   HARVARD REVIEW OF PSYCHIATRY

Accuracy of dementia diagnosis--a direct comparison between radiologists and a computerized method

(2008) S. Kloppel et al.   BRAIN