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Precision Health Database


Genomics & Health Impact Scan Database|Search|PHGKB

Last data update: Mar 30, 2023. (Total: 59025 Documents since 2012)
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Digital cognitive behavioral therapy for insomnia on depression and anxiety: a systematic review and meta-analysis
S Lee et al, NPJ Digital Medicine, March 25, 2023
Predicting Conversion from Subjective Cognitive Decline to Mild Cognitive Impairment and Alzheimer's Disease Dementia Using Ensemble Machine Learning.
Marta M Dolcet-Negre et al. Journal of Alzheimer's disease : JAD 2023
Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study.
Gerard Anmella et al. JMIR mHealth and uHealth 2023
A multicomponent digital intervention to promote help-seeking for mental health problems and suicide in sexual and gender diverse young adults: A randomized controlled trial.
Meng Han et al. PLoS medicine 2023 20(3) e1004197
Identification of High Likelihood of Dementia in Population-Based Surveys using Unsupervised Clustering: a Longitudinal Analysis.
Amin Gharbi-Meliani et al. medRxiv : the preprint server for health sciences 2023
Automated Video Analysis of Audio-Visual Approaches to Predict and Detect Mild Cognitive Impairment and Dementia in Older Adults.
Che-Sheng Chu et al. Journal of Alzheimer's disease : JAD 2023
Prediction of suicidality in bipolar disorder using variability of intrinsic brain activity and machine learning.
Shui Tian et al. Human brain mapping 2023
Bayesian network modeling of risk and prodromal markers of Parkinson's disease.
Meemansa Sood et al. PloS one 2023 18(2) e0280609
Using Machine Learning to Predict Cognitive Impairment Among Middle-Aged and Older Chinese: A Longitudinal Study.
Haihong Liu et al. International journal of public health 2023 681605322
An optimization for postpartum depression risk assessment and preventive intervention strategy based machine learning approaches.
Hao Liu et al. Journal of affective disorders 2023
Self-Management of Subclinical Common Mental Health Disorders (Anxiety, Depression and Sleep Disorders) Using Wearable Devices.
Tony Robinson et al. International journal of environmental research and public health 2023 20(3)
Multimodal predictions of treatment outcome in major depression: A comparison of data-driven predictors with importance ratings by clinicians.
Nicolas Rost et al. Journal of affective disorders 2023
Initial antidepressant choice by non-psychiatrists: Learning from large-scale electronic health records.
Yi-Han Sheu et al. General hospital psychiatry 2023 8122-31
Early detection of depression using a conversational AI bot: A non-clinical trial.
Payam Kaywan et al. PloS one 2023 18(2) e0279743
Development of a model to predict combined antidepressant medication and psychotherapy treatment response for depression among veterans.
Robert M Bossarte et al. Journal of affective disorders 2023
Measuring the performance of prediction models to personalize treatment choice.
Orestis Efthimiou et al. Statistics in medicine 2023
Association of Smartphone Use and Digital Addiction with Mental Health, Quality of Life, Motivation and Learning of Medical Students: A Two-Year Follow-Up Study.
Marise Machado de Oliveira et al. Psychiatry 2023 1-14
A machine learning approach to determine the influence of specific health conditions on self-rated health across education groups.
Gumà-Lao Jordi et al. BMC public health 2023 23(1) 131
The selfBACK artificial intelligence-based smartphone app can improve low back pain outcome even in patients with high levels of depression or stress.
Rughani G et al. European journal of pain (London, England) 2023
Challenges for Artificial Intelligence in Recognizing Mental Disorders.
Yan Wen-Jing et al. Diagnostics (Basel, Switzerland) 2023 13(1)
Measuring depression severity based on facial expression and body movement using deep convolutional neural network.
Liu Dongdong et al. Frontiers in psychiatry 2023 131017064
Development of medical device software for the screening and assessment of depression severity using data collected from a wristband-type wearable device: SWIFT study protocol.
Kishimoto Taishiro et al. Frontiers in psychiatry 2023 131025517
The Precision in Psychiatry (PIP) study: Testing an internet-based methodology for accelerating research in treatment prediction and personalisation.
Lee Chi Tak et al. BMC psychiatry 2023 23(1) 25
A hybrid machine learning model of depression estimation in home-based older adults: a 7-year follow-up study.
Lin Shaowu et al. BMC psychiatry 2022 22(1) 816
Determination of the motor status of patients with advanced Parkinson's disease under levodopa-carbidopa intestinal gel using a machine learning model.
Efthymiopoulou Efthymia et al. Acta neurologica Belgica 2022
Personalised depression forecasting using mobile sensor data and ecological momentary assessment.
Kathan Alexander et al. Frontiers in digital health 2022 4964582
Machine learning models for predicting risk of depression in Korean college students: Identifying family and individual factors.
Gil Minji et al. Frontiers in public health 2022 101023010
Machine learning can predict mild cognitive impairment in Parkinson's disease.
Amboni Marianna et al. Frontiers in neurology 2022 131010147
Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.
Yang Jiaxin et al. Frontiers in public health 2022 101049069
Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial.
Forman Evan M et al. Contemporary clinical trials 2022 107029
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