Published on in Vol 23 , No 5 (2021) :May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15708, first published .
Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Journals

  1. Bolívar S, Nieto-Reyes A, Rogers H. Supervised Classification of Healthcare Text Data Based on Context-Defined Categories. Mathematics 2022;10(12):2005 View
  2. Song J, Ojo M, Bowles K, McDonald M, Cato K, Rossetti S, Adams V, Chae S, Hobensack M, Kennedy E, Tark A, Kang M, Woo K, Barrón Y, Sridharan S, Topaz M. Detecting Language Associated With Home Healthcare Patient’s Risk for Hospitalization and Emergency Department Visit. Nursing Research 2022;71(4):285 View
  3. Young J, Bishop S, Humphrey C, Pavlacic J. A review of natural language processing in the identification of suicidal behavior. Journal of Affective Disorders Reports 2023;12:100507 View
  4. An R, Shen J, Xiao Y. Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies. Journal of Medical Internet Research 2022;24(12):e40589 View
  5. Martinez-Millana A, Saez-Saez A, Tornero-Costa R, Azzopardi-Muscat N, Traver V, Novillo-Ortiz D. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews. International Journal of Medical Informatics 2022;166:104855 View
  6. Khan N, Javed M. Use of Artificial Intelligence-Based Strategies for Assessing Suicidal Behavior and Mental Illness: A Literature Review. Cureus 2022 View
  7. Jang J, Yoon S, Son G, Kang M, Choeh J, Choi K. Predicting Personality and Psychological Distress Using Natural Language Processing: A Study Protocol. Frontiers in Psychology 2022;13 View
  8. Ikram M, Shaikh N, Vishwanatha J, Sambamoorthi U. Leading Predictors of COVID-19-Related Poor Mental Health in Adult Asian Indians: An Application of Extreme Gradient Boosting and Shapley Additive Explanations. International Journal of Environmental Research and Public Health 2022;20(1):775 View
  9. Arowosegbe A, Oyelade T. Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review. International Journal of Environmental Research and Public Health 2023;20(2):1514 View
  10. Yee T, Shrifan N, Al-Gburi A, Isa N, Akbar M. Prospect of Using Machine Learning-Based Microwave Nondestructive Testing Technique for Corrosion Under Insulation: A Review. IEEE Access 2022;10:88191 View
  11. Singh A, Singh J. Synthesis of Affective Expressions and Artificial Intelligence to Discover Mental Distress in Online Community. International Journal of Mental Health and Addiction 2022 View
  12. Ahmed A, Agus M, Alzubaidi M, Aziz S, Abd-Alrazaq A, Giannicchi A, Househ M. Overview of the role of big data in mental health: A scoping review. Computer Methods and Programs in Biomedicine Update 2022;2:100076 View
  13. Lekkas D, Gyorda J, Jacobson N. A machine learning investigation into the temporal dynamics of physical activity‐mediated emotional regulation in adolescents with anorexia nervosa and healthy controls. European Eating Disorders Review 2023;31(1):147 View
  14. Hobensack M, Song J, Scharp D, Bowles K, Topaz M. Machine learning applied to electronic health record data in home healthcare: A scoping review. International Journal of Medical Informatics 2023;170:104978 View
  15. Bhattacharya M, Roy S, Chattopadhyay S, Das A, Shetty S. A comprehensive survey on online social networks security and privacy issues: Threats, machine learning‐based solutions, and open challenges. SECURITY AND PRIVACY 2023;6(1) View
  16. Pettit R, Fullem R, Cheng C, Amos C. Artificial intelligence, machine learning, and deep learning for clinical outcome prediction. Emerging Topics in Life Sciences 2021;5(6):729 View
  17. Mezzi R, Yahyaoui A, Krir M, Boulila W, Koubaa A. Mental Health Intent Recognition for Arabic-Speaking Patients Using the Mini International Neuropsychiatric Interview (MINI) and BERT Model. Sensors 2022;22(3):846 View
  18. Bhardwaj R, Vaidya T, Poria S. Towards solving NLP tasks with optimal transport loss. Journal of King Saud University - Computer and Information Sciences 2022;34(10):10434 View
  19. Oyebode O, Fowles J, Steeves D, Orji R. Machine Learning Techniques in Adaptive and Personalized Systems for Health and Wellness. International Journal of Human–Computer Interaction 2022:1 View
  20. Harvey D, Lobban F, Rayson P, Warner A, Jones S. Natural Language Processing Methods and Bipolar Disorder: Scoping Review. JMIR Mental Health 2022;9(4):e35928 View
  21. Chiavi D, Haag C, Chan A, Kamm C, Sieber C, Stanikić M, Rodgers S, Pot C, Kesselring J, Salmen A, Rapold I, Calabrese P, Manjaly Z, Gobbi C, Zecca C, Walther S, Stegmayer K, Hoepner R, Puhan M, von Wyl V. The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing. JMIR Medical Informatics 2022;10(11):e37945 View
  22. Alabrah A, Alawadh H, Okon O, Meraj T, Rauf H. Gulf Countries’ Citizens’ Acceptance of COVID-19 Vaccines—A Machine Learning Approach. Mathematics 2022;10(3):467 View
  23. Lejeune A, Le Glaz A, Perron P, Sebti J, Baca-Garcia E, Walter M, Lemey C, Berrouiguet S. Artificial intelligence and suicide prevention: A systematic review. European Psychiatry 2022;65(1) View
  24. Ahmad S, Tarabochia A, Budahn L, Lemahieu A, Anderson B, Vashistha K, Karnatovskaia L, Gajic O. Feasibility of Extracting Meaningful Patient Centered Outcomes From the Electronic Health Record Following Critical Illness in the Elderly. Frontiers in Medicine 2022;9 View
  25. Lejeune A, Robaglia B, Walter M, Berrouiguet S, Lemey C. Use of Social Media Data to Diagnose and Monitor Psychotic Disorders: Systematic Review. Journal of Medical Internet Research 2022;24(9):e36986 View
  26. Liu Z, Peach R, Lawrance E, Noble A, Ungless M, Barahona M. Listening to Mental Health Crisis Needs at Scale: Using Natural Language Processing to Understand and Evaluate a Mental Health Crisis Text Messaging Service. Frontiers in Digital Health 2021;3 View
  27. Priyanka P, Azad S, Chakravarty R. Artificial intelligence (AI) literature in patents: a global landscape. Library Hi Tech News 2021;38(7):24 View
  28. Yogeswaran V, Morr C. Mental Health for Medical Students, what do we know today?. Procedia Computer Science 2022;198:307 View
  29. Dikaios K, Rempel S, Dumpala S, Oore S, Kiefte M, Uher R. Applications of Speech Analysis in Psychiatry. Harvard Review of Psychiatry 2023;31(1):1 View
  30. Chen Z, Kulkarni P, Galatzer-Levy I, Bigio B, Nasca C, Zhang Y. Modern views of machine learning for precision psychiatry. Patterns 2022;3(11):100602 View
  31. Wu C, Chen C, Su C, Chien Y, Dai H, Chen H. Augmenting DSM-5 diagnostic criteria with self-attention-based BiLSTM models for psychiatric diagnosis. Artificial Intelligence in Medicine 2023;136:102488 View
  32. Skaik R, Inkpen D. Predicting Depression in Canada by Automatic Filling of Beck’s Depression Inventory Questionnaire. IEEE Access 2022;10:102033 View
  33. Bhattacharya M, Bhat S, Tripathy S, Bansal A, Choudhary M. Improving biomedical named entity recognition through transfer learning and asymmetric tri-training. Procedia Computer Science 2023;218:2723 View
  34. Crema C, Attardi G, Sartiano D, Redolfi A. Natural language processing in clinical neuroscience and psychiatry: A review. Frontiers in Psychiatry 2022;13 View
  35. Tagliazucchi E. Language as a Window Into the Altered State of Consciousness Elicited by Psychedelic Drugs. Frontiers in Pharmacology 2022;13 View
  36. Abayomi-Alli O, Damaševičius R, Qazi A, Adedoyin-Olowe M, Misra S. Data Augmentation and Deep Learning Methods in Sound Classification: A Systematic Review. Electronics 2022;11(22):3795 View
  37. Cohen A, Rodriguez Z, Warren K, Cowan T, Masucci M, Edvard Granrud O, Holmlund T, Chandler C, Foltz P, Strauss G. Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation. Schizophrenia Bulletin 2022;48(5):939 View
  38. ENSARİ T, ENSARİ B, DAĞTEKİN M. Violence Detection with Machine Learning: A Sociodemographic Approach. European Journal of Science and Technology 2023 View
  39. Pethani F, Dunn A. Natural language processing for clinical notes in dentistry: A systematic review. Journal of Biomedical Informatics 2023;138:104282 View
  40. Timmons A, Duong J, Simo Fiallo N, Lee T, Vo H, Ahle M, Comer J, Brewer L, Frazier S, Chaspari T. A Call to Action on Assessing and Mitigating Bias in Artificial Intelligence Applications for Mental Health. Perspectives on Psychological Science 2022:174569162211344 View
  41. Keikha A. Generalized hesitant fuzzy numbers and their application in solving MADM problems based on TOPSIS method. Soft Computing 2022;26(10):4673 View
  42. McDermott M, Nestor B, Szolovits P. Clinical Artificial Intelligence. Clinics in Laboratory Medicine 2023;43(1):29 View
  43. Shaheen M. AI in Healthcare: medical and socio-economic benefits and challenges. SSRN Electronic Journal 2021 View
  44. Fallah A, Aghdam M. Physics-informed neural network for bending and free vibration analysis of three-dimensional functionally graded porous beam resting on elastic foundation. Engineering with Computers 2023 View

Books/Policy Documents

  1. V. S. A. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease. View
  2. Chen X, Genc Y. Artificial Intelligence in HCI. View
  3. Nguyen N, Labonte-Lemoyne E, Gregoire Y, Radanielina-Hita M, Senecal S. HCI International 2022 – Late Breaking Posters. View
  4. Pangsrisomboon P, Pyae A, Thawitsri N, Liulak S. Well-Being in the Information Society: When the Mind Breaks. View
  5. Ayatollahi H. Data Science with Semantic Technologies. View
  6. Mishra S, Abbas M, Jindal K, Narayan J, Dwivedy S. Revolutions in Product Design for Healthcare. View
  7. Li R, Li H, Tang B, Au W. Current State of Art in Artificial Intelligence and Ubiquitous Cities. View
  8. Tan T, Lim S, Qiu Y, Miao C. Social Computing and Social Media: Design, User Experience and Impact. View
  9. Ahmed U, Lin J, Srivastava G. Advances in Knowledge Discovery and Data Mining. View