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Public Health Genomics and Precision Health Knowledge Base (v9.0)
PHGKB
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Last data update: May 03, 2024
. (Total: 63770 Documents since 2012)
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The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review.
Fabeha Zafar et al. Cureus 2024 16(3) e56472
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Investigating machine learning and natural language processing techniques applied for detecting eating disorders: a systematic literature review.
Ghofrane Merhbene et al. Front Psychiatry 2024 151319522
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Predicting state level suicide fatalities in the united states with realtime data and machine learning.
Devashru Patel et al. Npj Ment Health Res 2024 3(1) 3
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Identifying Psychosis Episodes in Psychiatric Admission Notes via Rule-based Methods, Machine Learning, and Pre-Trained Language Models.
Yining Hua et al. medRxiv 2024
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Identifying Psychosis Episodes in Psychiatric Admission Notes via Rule-based Methods, Machine Learning, and Pre-Trained Language Models.
Yining Hua et al. Res Sq 2024
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Machine learning in mental health and its relationship with epidemiological practice.
Marcos DelPozo-Banos et al. Front Psychiatry 2024 151347100
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Validation of a Multivariable Model to Predict Suicide Attempt in a Mental Health Intake Sample.
Santiago Papini et al. JAMA Psychiatry 2024
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Digital Tools to Facilitate the Detection and Treatment of Bipolar Disorder: Key Developments and Future Directions.
Taiane de Azevedo Cardoso et al. JMIR Ment Health 2024 11e58631
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Promoting Physical Activity Among Workers for Better Mental Health: An mHealth Intervention With Deep Learning.
Kazuhiro Watanabe et al. J UOEH 2024 46(1) 119-122
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Identifying non-adult attention-deficit/hyperactivity disorder individuals using a stacked machine learning algorithm using administrative data population registers in a universal healthcare system.
David Roche et al. JCPP Adv 2024 4(1) e12193
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Clinical Practice Guidelines on using artificial intelligence and gadgets for mental health and well-being.
Vipul Singh et al. Indian J Psychiatry 2024 66(Suppl 2) S414-S419
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Cloud-Based Machine Learning Platform to Predict Clinical Outcomes at Home for Patients With Cardiovascular Conditions Discharged From Hospital: Clinical Trial.
Phillip C Yang et al. JMIR Cardio 2024 8e45130
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Implementation of a Clinical, Patient-Level Dashboard at a Mental Health Hospital: Lessons Learned from Two Pilot Clinics.
Masooma Hassan et al. Stud Health Technol Inform 2024 31241-46
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Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques.
Simran Saggu et al. BMC Med Inform Decis Mak 2024 24(1) 42
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Monitoring Mental Health: Legal and Ethical Considerations of Using Artificial Intelligence in Psychiatric Wards.
Barry Solaiman et al. Am J Law Med 2024 49(2-3) 250-266
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Predicting suicide death after emergency department visits with mental health or self-harm diagnoses.
Gregory E Simon et al. Gen Hosp Psychiatry 2024 8713-19
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Mental Health Counseling From Conversational Content With Transformer-Based Machine Learning.
Zac E Imel et al. JAMA Netw Open 2024 7(1) e2352590
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Selectively predicting the onset of ADHD, oppositional defiant disorder, and conduct disorder in early adolescence with high accuracy.
Nina de Lacy et al. Front Psychiatry 2023 141280326
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Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being
H Li, NPJ Digital Medicine, December 19, 2023
End-to-end multimodal system for depression detection from online recordings.
Mateusz Kowalewski et al. Annu Int Conf IEEE Eng Med Biol Soc 2023 20231-4
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Replicability and reproducibility of predictive models for diagnosis of depression among young adults using Electronic Health Records.
David Nickson et al. Diagn Progn Res 2023 7(1) 25
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Using Machine Learning to Predict Antidepressant Treatment Outcome From Electronic Health Records.
Zhenxing Xu et al. Psychiatr Res Clin Pract 2023 5(4) 118-125
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Natural language processing system for rapid detection and intervention of mental health crisis chat messages.
Akshay Swaminathan et al. NPJ Digit Med 2023 6(1) 213
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mHealth Intervention to Promote Physical Activity Among Employees Using a Deep Learning Model for Passive Monitoring of Depression and Anxiety: Single-Arm Feasibility Trial.
Kazuhiro Watanabe et al. JMIR Form Res 2023 7e51334
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Ten Simple Rules for Using Machine Learning in Mental Health Research.
Joaquim Radua et al. Biol Psychiatry 2023
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A holistic approach to integrating patient, family, and lived experience voices in the development of the BrainHealth Databank: a digital learning health system to enable artificial intelligence in the clinic.
Joanna Yu et al. Front Health Serv 2023 31198195
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Current challenges and potential solutions to the use of digital health technologies in evidence generation: a narrative review.
Hassan Mumtaz et al. Front Digit Health 2023 51203945
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Effect of Telemedicine Use on Medical Spending and Health Care Utilization: A Machine Learning Approach.
Ayesha Jamal et al. AJPM Focus 2023 2(3) 100127
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Exploring the Role of Artificial Intelligence in Mental Healthcare: Progress, Pitfalls, and Promises.
Gemma Espejo et al. Cureus 2023 15(9) e44748
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Revolutionizing healthcare: the role of artificial intelligence in clinical practice.
Shuroug A Alowais et al. BMC Med Educ 2023 23(1) 689
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Page last reviewed:
Feb 1, 2024
Page last updated:
May 03, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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