This paper is in the following e-collection/theme issue:

Digital Health Reviews (1289) Machine Learning (1465) Natural Language Processing (692) Clinical Information and Decision Making (1407) Artificial Intelligence (1371) Decision Support for Health Professionals (1185) Diagnostic Tools in Mental Health (242)

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

Authors of this article:

Aziliz Le Glaz1 Author Orcid Image ;   Yannis Haralambous2 Author Orcid Image ;   Deok-Hee Kim-Dufor1 Author Orcid Image ;   Philippe Lenca2 Author Orcid Image ;   Romain Billot2 Author Orcid Image ;   Taylor C Ryan3 Author Orcid Image ;   Jonathan Marsh4 Author Orcid Image ;   Jordan DeVylder4 Author Orcid Image ;   Michel Walter1, 5 Author Orcid Image ;   Sofian Berrouiguet1, 2, 5, 6 Author Orcid Image ;   Christophe Lemey1, 2, 5 Author Orcid Image
Article Authors Cited by (219) Tweetations (11) Metrics

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 2024;22(4):1921 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 2023;39(9):1938 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 2023;18(5):1062 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 2024;40(1):437 View
  45. Tida V, Hsu S, Hei X. A Unified Training Process for Fake News Detection Based on Finetuned Bidirectional Encoder Representation from Transformers Model. Big Data 2024;12(4):331 View
  46. Khan M, Afrin F, Prity F, Ahammad I, Fatema S, Prosad R, Hasan M, Uddin M, Zayed-Us-Salehin . An effective approach for early liver disease prediction and sensitivity analysis. Iran Journal of Computer Science 2023;6(4):277 View
  47. Zhu J, Li Z, Zhang X, Zhang Z, Hu B. Public Attitudes Toward Anxiety Disorder on Sina Weibo: Content Analysis. Journal of Medical Internet Research 2023;25:e45777 View
  48. Jin Z, Zhang H, Tai M, Yang Y, Yao Y, Guo Y. Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation. Journal of Medical Internet Research 2023;25:e43153 View
  49. Pool-Cen J, Carlos-Martínez H, Hernández-Chan G, Sánchez-Siordia O. Detection of Depression-Related Tweets in Mexico Using Crosslingual Schemes and Knowledge Distillation. Healthcare 2023;11(7):1057 View
  50. Dujić Rodić L, Stančić I, Čoko D, Perković T, Granić A. Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance. Electronics 2023;12(8):1951 View
  51. Allen K, Hood D, Cummins J, Kasturi S, Mendonca E, Vest J. Natural language processing-driven state machines to extract social factors from unstructured clinical documentation. JAMIA Open 2023;6(2) View
  52. Di Cara N, Maggio V, Davis O, Haworth C. Methodologies for Monitoring Mental Health on Twitter: Systematic Review. Journal of Medical Internet Research 2023;25:e42734 View
  53. Atkinson C. Cheap, Quick, and Rigorous: Artificial Intelligence and the Systematic Literature Review. Social Science Computer Review 2024;42(2):376 View
  54. Mehtab V, Alam S, Povari S, Nakka L, Soujanya Y, Chenna S. Reduced Order Machine Learning Models for Accurate Prediction of CO2 Capture in Physical Solvents. Environmental Science & Technology 2023;57(46):18091 View
  55. Wright-Berryman J, Cohen J, Haq A, Black D, Pease J. Virtually screening adults for depression, anxiety, and suicide risk using machine learning and language from an open-ended interview. Frontiers in Psychiatry 2023;14 View
  56. Mu J, Gong J, Lin P, Zhang M, Wu K. Machine learning methods revealed the roles of immune-metabolism related genes in immune infiltration, stemness, and prognosis of neuroblastoma. Cancer Biomarkers 2023;38(2):241 View
  57. Uddin K, Prity F, Tasnim M, Jannat S, Faruk M, Islam J, Murad S, Adhikary A, Bairagi A. Machine Learning-Based Screening Solution for COVID-19 Cases Investigation: Socio-Demographic and Behavioral Factors Analysis and COVID-19 Detection. Human-Centric Intelligent Systems 2023;3(4):441 View
  58. Lu T, Liu X, Sun J, Bao Y, Schuller B, Han Y, Lu L. Bridging the gap between artificial intelligence and mental health. Science Bulletin 2023;68(15):1606 View
  59. Allahqoli L, Ghiasvand M, Mazidimoradi A, Salehiniya H, Alkatout I. Diagnostic and Management Performance of ChatGPT in Obstetrics and Gynecology. Gynecologic and Obstetric Investigation 2023;88(5):310 View
  60. Magoc T, Everson R, Harle C. Enhancing an enterprise data warehouse for research with data extracted using natural language processing. Journal of Clinical and Translational Science 2023;7(1) View
  61. Parker R, Mancini K, Abram M. Natural Language Processing Enhanced Qualitative Methods: An Opportunity to Improve Health Outcomes. International Journal of Qualitative Methods 2023;22 View
  62. Atzil-Slonim D, Penedo J, Lutz W. Leveraging Novel Technologies and Artificial Intelligence to Advance Practice-Oriented Research. Administration and Policy in Mental Health and Mental Health Services Research 2024;51(3):306 View
  63. Zippi Z, Cortopassi I, Johnson E, McDermott S, Mergo P, Petranovic M, Price M, Stowell J, Little B. U.S. Newspaper Coverage of Lung Cancer Screening From 2010 to 2022. American Journal of Roentgenology 2023;221(2):258 View
  64. Kolasa K, Admassu B, Hołownia-Voloskova M, Kędzior K, Poirrier J, Perni S. Systematic reviews of machine learning in healthcare: a literature review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(1):63 View
  65. Terra M, Baklola M, Ali S, El-Bastawisy K. Opportunities, applications, challenges and ethical implications of artificial intelligence in psychiatry: a narrative review. The Egyptian Journal of Neurology, Psychiatry and Neurosurgery 2023;59(1) View
  66. Liu Y. Depression clinical detection model based on social media: a federated deep learning approach. The Journal of Supercomputing 2024;80(6):7931 View
  67. Sun R, Li X, Shen J, Jin W. An effective hybrid automated Chinese scoring system for medical education. Expert Systems with Applications 2023;234:121114 View
  68. Alqahtani T, Badreldin H, Alrashed M, Alshaya A, Alghamdi S, bin Saleh K, Alowais S, Alshaya O, Rahman I, Al Yami M, Albekairy A. The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research. Research in Social and Administrative Pharmacy 2023;19(8):1236 View
  69. Furukawa T, Iwata S, Horikoshi M, Sakata M, Toyomoto R, Luo Y, Tajika A, Kudo N, Aramaki E. Harnessing AI to Optimize Thought Records and Facilitate Cognitive Restructuring in Smartphone CBT: An Exploratory Study. Cognitive Therapy and Research 2023;47(6):887 View
  70. Bin C, Li Q, Tang J, Dai C, Jiang T, Xie X, Qiu M, Chen L, Yang S. Machine learning models for predicting the risk factor of carotid plaque in cardiovascular disease. Frontiers in Cardiovascular Medicine 2023;10 View
  71. Msosa Y, Grauslys A, Zhou Y, Wang T, Buchan I, Langan P, Foster S, Walker M, Pearson M, Folarin A, Roberts A, Maskell S, Dobson R, Kullu C, Kehoe D. Trustworthy Data and AI Environments for Clinical Prediction: Application to Crisis-Risk in People With Depression. IEEE Journal of Biomedical and Health Informatics 2023;27(11):5588 View
  72. Shaik T, Tao X, Li L, Xie H, Velásquez J. A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom. Information Fusion 2024;102:102040 View
  73. Rajkishan S, Meitei A, Singh A. Role of AI/ML in the study of mental health problems of the students: a bibliometric study. International Journal of System Assurance Engineering and Management 2024;15(5):1615 View
  74. Khorasani M, Kahani M, Yazdi S, Hajiaghaei-Keshteli M. Towards finding the lost generation of autistic adults: A deep and multi-view learning approach on social media. Knowledge-Based Systems 2023;276:110724 View
  75. Goswami P, Bhatia D. Application of Machine Learning in FPGA EDA Tool Development. IEEE Access 2023;11:109564 View
  76. Karmalkar P, Gurulingappa H, Spies E, Flynn J. Artificial intelligence-driven approach for patient-focused drug development. Frontiers in Artificial Intelligence 2023;6 View
  77. Zantvoort K, Scharfenberger J, Boß L, Lehr D, Funk B. Finding the Best Match — a Case Study on the (Text-)Feature and Model Choice in Digital Mental Health Interventions. Journal of Healthcare Informatics Research 2023;7(4):447 View
  78. Hossain M, Maruf M, Khan M, Prity F, Fatema S, Ejaz M, Khan M. Heart disease prediction using distinct artificial intelligence techniques: performance analysis and comparison. Iran Journal of Computer Science 2023;6(4):397 View
  79. Zhang H, Wang H, Han S, Li W, Zhuang L. Detecting depression tendency with multimodal features. Computer Methods and Programs in Biomedicine 2023;240:107702 View
  80. Muñoz S, Iglesias C. Detection of the Severity Level of Depression Signs in Text Combining a Feature-Based Framework with Distributional Representations. Applied Sciences 2023;13(21):11695 View
  81. Magoc T, Allen K, McDonnell C, Russo J, Cummins J, Vest J, Harle C. Generalizability and portability of natural language processing system to extract individual social risk factors. International Journal of Medical Informatics 2023;177:105115 View
  82. Raveau M, Goñi J, Rodríguez J, Paiva-Mack I, Barriga F, Hermosilla M, Fuentes-Bravo C, Eyheramendy S. Natural language processing analysis of the psychosocial stressors of mental health disorders during the pandemic. npj Mental Health Research 2023;2(1) View
  83. Gholipour M, Khajouei R, Amiri P, Hajesmaeel Gohari S, Ahmadian L. Extracting cancer concepts from clinical notes using natural language processing: a systematic review. BMC Bioinformatics 2023;24(1) View
  84. Engineer M, Kot S, Dixon E. Investigating the Readability and Linguistic, Psychological, and Emotional Characteristics of Digital Dementia Information Written in the English Language: Multitrait-Multimethod Text Analysis. JMIR Formative Research 2023;7:e48143 View
  85. Chaturvedi J, Chance N, Mirza L, Vernugopan V, Velupillai S, Stewart R, Roberts A. Development of a Corpus Annotated With Mentions of Pain in Mental Health Records: Natural Language Processing Approach. JMIR Formative Research 2023;7:e45849 View
  86. Cunningham P, Gilmore J, Naar S, Preston S, Eubanks C, Hubig N, McClendon J, Ghosh S, Ryan-Pettes S. Opening the Black Box of Family-Based Treatments: An Artificial Intelligence Framework to Examine Therapeutic Alliance and Therapist Empathy. Clinical Child and Family Psychology Review 2023;26(4):975 View
  87. Yang E, Kornfield R, Liu Y, Chih M, Sarma P, Gustafson D, Curtin J, Shah D. Using Machine Learning of Online Expression to Explain Recovery Trajectories: Content Analytic Approach to Studying a Substance Use Disorder Forum. Journal of Medical Internet Research 2023;25:e45589 View
  88. Fu J, Yang J, Li Q, Huang D, Yang H, Xie X, Xu H, Zhang M, Zheng C. What can we learn from a Chinese social media used by glaucoma patients?. BMC Ophthalmology 2023;23(1) View
  89. Chen J, He F, Wu Q, Wang L, Zhu X, Qi Y, Wu J, Shi Y. Identifying self-reported health-related problems in home-based rehabilitation of older patients after hip replacement in China: a machine learning study based on Omaha system theory. BMC Medical Informatics and Decision Making 2023;23(1) View
  90. Romano M, Shih L, Paschalidis I, Au R, Kolachalama V. Large Language Models in Neurology Research and Future Practice. Neurology 2023;101(23):1058 View
  91. Li T, Chen J, Law F, Li C, Chan N, Chan J, Chau S, Liu Y, Li S, Zhang J, Leung K, Wing Y. Detection of Suicidal Ideation in Clinical Interviews for Depression Using Natural Language Processing and Machine Learning: Cross-Sectional Study. JMIR Medical Informatics 2023;11:e50221 View
  92. Wang Y, Yu Y, Liu Y, Ma Y, Pang P. Predicting Patients' Satisfaction With Mental Health Drug Treatment Using Their Reviews: Unified Interchangeable Model Fusion Approach. JMIR Mental Health 2023;10:e49894 View
  93. Atkinson C. ChatGPT and computational-based research: benefits, drawbacks, and machine learning applications. Discover Artificial Intelligence 2023;3(1) View
  94. Park J, Kim H. Strategic Formation of CEO Apologies: Emulating Post-Crisis Public Statements Through GPT-4. Customer Needs and Solutions 2024;11(1) View
  95. Almufareh M, Tehsin S, Humayun M, Kausar S. Intellectual Disability and Technology: An Artificial Intelligence Perspective and Framework. Journal of Disability Research 2023;2(4) View
  96. Arora M, Singh J, Singh A. Development of intelligent system based on synthesis of affective signals and deep neural networks to foster mental health of the Indian virtual community. Social Network Analysis and Mining 2024;14(1) View
  97. Khoo L, Lim M, Chong C, McNaney R. Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches. Sensors 2024;24(2):348 View
  98. Han H, Asif M, Awwad E, Sarhan N, Ghadi Y, Xu B. Innovative deep learning techniques for monitoring aggressive behavior in social media posts. Journal of Cloud Computing 2024;13(1) View
  99. Weisenburger R, Mullarkey M, Labrada J, Labrousse D, Yang M, MacPherson A, Hsu K, Ugail H, Shumake J, Beevers C. Conversational assessment using artificial intelligence is as clinically useful as depression scales and preferred by users. Journal of Affective Disorders 2024;351:489 View
  100. Bertin T. La lexie intelligence artificielle dans les titres de presse français – échos d’une révolution technologique. Linguodidactica 2023;27:5 View
  101. Chemnad K, Othman A. Digital accessibility in the era of artificial intelligence—Bibliometric analysis and systematic review. Frontiers in Artificial Intelligence 2024;7 View
  102. Ortiz-Garces I, Govea J, Andrade R, Villegas-Ch W. Optimizing Chatbot Effectiveness through Advanced Syntactic Analysis: A Comprehensive Study in Natural Language Processing. Applied Sciences 2024;14(5):1737 View
  103. Sim J, Huang X, Horan M, Baker J, Huang I. Using natural language processing to analyze unstructured patient-reported outcomes data derived from electronic health records for cancer populations: a systematic review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(4):467 View
  104. Eyre H, Alba P, Gibson C, Gatsby E, Lynch K, Patterson O, DuVall S. Bridging information gaps in menopause status classification through natural language processing. JAMIA Open 2024;7(1) View
  105. Nissar G, Khan R, Mushtaq S, Lone S, Moon A. RETRACTED ARTICLE: IoT in healthcare: a review of services, applications, key technologies, security concerns, and emerging trends. Multimedia Tools and Applications 2024;83(33):80283 View
  106. Pourkeyvan A, Safa R, Sorourkhah A. Harnessing the Power of Hugging Face Transformers for Predicting Mental Health Disorders in Social Networks. IEEE Access 2024;12:28025 View
  107. Romagnoli A, Ferrara F, Langella R, Zovi A. Healthcare Systems and Artificial Intelligence: Focus on Challenges and the International Regulatory Framework. Pharmaceutical Research 2024;41(4):721 View
  108. Yang L, Wang T, Zhang J, Kang S, Xu S, Wang K. Deep learning–based automatic segmentation of meningioma from T1-weighted contrast-enhanced MRI for preoperative meningioma differentiation using radiomic features. BMC Medical Imaging 2024;24(1) View
  109. Jiang F, Li X, Liu L, Xie Z, Wu X, Wang Y. Automated machine learning-based model for the prediction of pedicle screw loosening after degenerative lumbar fusion surgery. BioScience Trends 2024;18(1):83 View
  110. Chadaga K, Prabhu S, Sampathila N, Chadaga R, Bhat D, Sharma A, Swathi K. SADXAI: Predicting social anxiety disorder using multiple interpretable artificial intelligence techniques. SLAS Technology 2024;29(2):100129 View
  111. Alkahtani H, Aldhyani T, Alqarni A. Artificial Intelligence Models to Predict Disability for Mental Health Disorders. Journal of Disability Research 2024;3(3) View
  112. Haase E, Sassen R. Uncovering lobbying strategies in sustainable finance disclosure regulations using machine learning. Journal of Environmental Management 2024;356:120562 View
  113. Zafar F, Fakhare Alam L, Vivas R, Wang J, Whei S, Mehmood S, Sadeghzadegan A, Lakkimsetti M, Nazir Z. The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review. Cureus 2024 View
  114. Kuziemsky C, Chrimes D, Minshall S, Mannerow M, Lau F. AI Quality Standards in Health Care: Rapid Umbrella Review. Journal of Medical Internet Research 2024;26:e54705 View
  115. Khan A, Ali R. Unraveling minds in the digital era: a review on mapping mental health disorders through machine learning techniques using online social media. Social Network Analysis and Mining 2024;14(1) View
  116. Keyvanpour M, Pourebrahim B, Mehrmolaei S. EADR: an ensemble learning method for detecting adverse drug reactions from twitter. Social Network Analysis and Mining 2024;14(1) View
  117. Zheng C, Tao Y, Zhang J, Xun L, Li T, Yan Q. TISE-LSTM: A LSTM model for precipitation nowcasting with temporal interactions and spatial extract blocks. Neurocomputing 2024;590:127700 View
  118. Rizvi S, Arif A. Guest Editorial: Foreword of the Special Issue on Real-World Applications of Machine Learning. Electronics 2024;13(8):1586 View
  119. Varalakshmi D, Tharaheswari M, Anand T, Saravanan K. Transforming oral cancer care: The promise of deep learning in diagnosis. Oral Oncology Reports 2024;10:100482 View
  120. Naidu P, Ruchitha M, Yaswanth P, Harika B, Prabhu P, Deepthi Sree G. Mental Health Detection using Machine Learning. International Journal of Innovative Science and Research Technology (IJISRT) 2024:760 View
  121. Franco D’Souza R, Mathew M, Amanullah S, Edward Thornton J, Mishra V, E M, Louis Palatty P, Surapaneni K. Navigating merits and limits on the current perspectives and ethical challenges in the utilization of artificial intelligence in psychiatry – An exploratory mixed methods study. Asian Journal of Psychiatry 2024;97:104067 View
  122. Oikonomou E, Karvelis P, Giannakeas N, Vrachatis A, Glavas E, Tzallas A. How natural language processing derived techniques are used on biological data: a systematic review. Network Modeling Analysis in Health Informatics and Bioinformatics 2024;13(1) View
  123. Alhuwaydi A. Exploring the Role of Artificial Intelligence in Mental Healthcare: Current Trends and Future Directions – A Narrative Review for a Comprehensive Insight. Risk Management and Healthcare Policy 2024;Volume 17:1339 View
  124. Bauer B, Norel R, Leow A, Rached Z, Wen B, Cecchi G. Using Large Language Models to Understand Suicidality in a Social Media–Based Taxonomy of Mental Health Disorders: Linguistic Analysis of Reddit Posts. JMIR Mental Health 2024;11:e57234 View
  125. Sikström S, Valavičiūtė I, Kuusela I, Evors N. Question-based computational language approach outperforms rating scales in quantifying emotional states. Communications Psychology 2024;2(1) View
  126. Gao W, Lu L, Yin X. Editorial: AI approach to the psychiatric diagnosis and prediction. Frontiers in Psychiatry 2024;15 View
  127. Lefkovitz I, Walsh S, Blank L, Jetté N, Kummer B. Direct Clinical Applications of Natural Language Processing in Common Neurological Disorders: Scoping Review. JMIR Neurotechnology 2024;3:e51822 View
  128. Soyarslan C, Pradas M. Physics-informed machine learning in asymptotic homogenization of elliptic equations. Computer Methods in Applied Mechanics and Engineering 2024;427:117043 View
  129. Quillivic R, Gayraud F, Auxéméry Y, Vanni L, Peschanski D, Eustache F, Dayan J, Mesmoudi S. Interdisciplinary approach to identify language markers for post-traumatic stress disorder using machine learning and deep learning. Scientific Reports 2024;14(1) View
  130. Ren Y, Yang M, Pan H, Farhat M, Enis Cetin A, Chen P. PT Symmetry-Enabled Physically Unclonable Functions for Anti-Counterfeiting RF Tags. IEEE Transactions on Antennas and Propagation 2024;72(6):5129 View
  131. Mazur M, Krukow P. The Significance of Natural Language Processing and Machine Learning in Schizophasia Description. Identification of Research Trends and Perspectives in Schizophrenia Language Studies. Current Problems of Psychiatry 2024;25:127 View
  132. Di Basilio D, King L, Lloyd S, Michael P, Shardlow M. Asking questions that are “close to the bone”: integrating thematic analysis and natural language processing to explore the experiences of people with traumatic brain injuries engaging with patient-reported outcome measures. Frontiers in Digital Health 2024;6 View
  133. Moreno-Álvarez S, Paoletti M, Sanchez-Fernandez A, Rico-Gallego J, Han L, Haut J. Federated learning meets remote sensing. Expert Systems with Applications 2024;255:124583 View
  134. Villarreal-Zegarra D, Reategui-Rivera C, García-Serna J, Quispe-Callo G, Lázaro-Cruz G, Centeno-Terrazas G, Galvez-Arevalo R, Escobar-Agreda S, Dominguez-Rodriguez A, Finkelstein J. Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis. JMIR Mental Health 2024;11:e59560 View
  135. Yasin Y, Al‐Hamad A, Metersky K, Kehyayan V. Incorporation of artificial intelligence into nursing research: A scoping review. International Nursing Review 2024 View
  136. Osman M, Cooper R, Sayer A, Witham M. The use of natural language processing for the identification of ageing syndromes including sarcopenia, frailty and falls in electronic healthcare records: a systematic review. Age and Ageing 2024;53(7) View
  137. Wiederhold B. Parsing Platforms: Natural Language Processing and Public Mental Health. Cyberpsychology, Behavior, and Social Networking 2024;27(8):521 View
  138. Zheng F. Development of a Big Data Analysis and Management Decision Support System for Student Mental Health in Higher Education. Applied Mathematics and Nonlinear Sciences 2024;9(1) View
  139. Derner E, Kučera D, Oliver N, Zahálka J. Can ChatGPT read who you are?. Computers in Human Behavior: Artificial Humans 2024;2(2):100088 View
  140. Pérez Gamboa A, Díaz-Guerra D. Artificial Intelligence for the development of qualitative studies. LatIA 2023;1:4 View
  141. Alhuzali H, Alasmari A, Alsaleh H. MentalQA: An Annotated Arabic Corpus for Questions and Answers of Mental Healthcare. IEEE Access 2024;12:101155 View
  142. Pilowsky J, Choi J, Saavedra A, Daher M, Nguyen N, Williams L, Jones S. Natural language processing in the intensive care unit: A scoping review. Critical Care and Resuscitation 2024;26(3):210 View
  143. Cosic K, Kopilas V, Jovanovic T. War, emotions, mental health, and artificial intelligence. Frontiers in Psychology 2024;15 View
  144. Laricheva M, Liu Y, Shi E, Wu A. Scoping review on natural language processing applications in counselling and psychotherapy. British Journal of Psychology 2024 View
  145. Aidam D, Benuwa B, Oppong S, Nwiah E. Sentiment and emotion analysis using pretrained deep learning models. Journal of Data, Information and Management 2024;6(3):277 View
  146. Águila Ramírez L. Artificial Intelligence in Psychological Diagnosis and Intervention. LatIA 2024;1:26 View
  147. Collin A, Ayuso-Muñoz A, Tejera-Nevado P, Prieto-Santamaría L, Verdejo-García A, Díaz-Batanero C, Fernández-Calderón F, Albein-Urios N, Lozano Ó, Rodríguez-González A. Analyzing Dropout in Alcohol Recovery Programs: A Machine Learning Approach. Journal of Clinical Medicine 2024;13(16):4825 View
  148. Bhattacharyya R, Chakraborty K, Neogi R. ChatGPT and its application in the field of mental health. Journal of SAARC Psychiatric Federation 2023;1(1):6 View
  149. Guo Z, Lai A, Thygesen J, Farrington J, Keen T, Li K. Large Language Models for Mental Health Applications: Systematic Review. JMIR Mental Health 2024;11:e57400 View
  150. Zhang Z, Zhu J, Guo Z, Zhang Y, Li Z, Hu B. Natural Language Processing for Depression Prediction on Sina Weibo: Method Study and Analysis. JMIR Mental Health 2024;11:e58259 View
  151. Jung S, Murthy D, Bateineh B, Loukas A, Wilkinson A. The Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e55591 View
  152. Milasan L. Unveiling the Transformative Potential of AI-Generated Imagery in Enriching Mental Health Research. Qualitative Health Research 2024 View
  153. Merayo N, Ayuso-Lanchares A, González-Sanguino C. Machine learning and natural language processing to assess the emotional impact of influencers’ mental health content on Instagram. PeerJ Computer Science 2024;10:e2251 View
  154. Bhuyan D, Bhuyan T. The Future of Psychiatric Research. Academic Bulletin of Mental Health 2024;2:51 View
  155. Ogunwale A, Smith A, Fakorede O, Ogunlesi A. Artificial intelligence and forensic mental health in Africa: a narrative review. International Review of Psychiatry 2024:1 View
  156. Wang J, Jin X. Commentary: Psychometric properties of the modified Suicide Stroop Task (M-SST) in patients with suicide risk and healthy controls. Frontiers in Psychology 2024;15 View
  157. Mourad J, Daniels K, Bogaerts K, Desseilles M, Bonnechère B. Innovative Digital Phenotyping Method to Assess Body Representations in Autistic Adults: A Perspective on Multisensor Evaluation. Sensors 2024;24(20):6523 View
  158. Grothman A, Ma W, Tickner K, Martin E, Southern D, Quan H. Case Identification of Depression in Inpatient Electronic Medical Records: Scoping Review. JMIR Medical Informatics 2024;12:e49781 View
  159. Nehmeh B, Rebehmed J, Nehmeh R, Taleb R, Akoury E. Unlocking therapeutic frontiers: harnessing artificial intelligence in drug discovery for neurodegenerative diseases. Drug Discovery Today 2024;29(12):104216 View
  160. Singh S, Gambill J, Attalla M, Fatima R, Gill A, Siddiqui H. Evaluating the Clinical Validity and Reliability of Artificial Intelligence-Enabled Diagnostic Tools in Neuropsychiatric Disorders. Cureus 2024 View
  161. Workman T, Ahmed A, Sheriff H, Raman V, Zhang S, Shao Y, Faselis C, Fonarow G, Zeng-Treitler Q. ChatGPT-4 extraction of heart failure symptoms and signs from electronic health records. Progress in Cardiovascular Diseases 2024 View
  162. Hutto A, Zikry T, Bohac B, Rose T, Staebler J, Slay J, Cheever C, Kosorok M, Nash R. Using a natural language processing toolkit to classify electronic health records by psychiatric diagnosis. Health Informatics Journal 2024;30(4) View
  163. Morgan P, Cogan N. Using artificial intelligence to address mental health inequalities: co-creating machine learning algorithms with key stakeholders and citizen engagement. Journal of Public Mental Health 2024 View
  164. Alemán Acuña R, Pereira Montiel E, Torres Silva E, Montoya Arenas D. Procesamiento de lenguaje natural en la Salud Mental: Revisión de alcance. Revista Iberoamericana de Psicología 2024;17(2):11 View
  165. Teferra B, Rueda A, Pang H, Valenzano R, Samavi R, Krishnan S, Bhat V. Screening for Depression Using Natural Language Processing: Literature Review. Interactive Journal of Medical Research 2024;13:e55067 View
  166. Singhal S, Cooke D, Villareal R, Stoddard J, Lin C, Dempsey A. Machine Learning for Mental Health: Applications, Challenges, and the Clinician's Role. Current Psychiatry Reports 2024 View
  167. Gokhale A. Countering flaws in algorithm design and applications: a Delphi study. AI & SOCIETY 2024 View
  168. Chustecki M. Benefits and Risks of AI in Health Care: Narrative Review. Interactive Journal of Medical Research 2024;13:e53616 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
  10. Kumar V, Medda G, Recupero D, Riboni D, Helaoui R, Fenu G. Advances in Bias and Fairness in Information Retrieval. View
  11. Ozsonmez D, Acarman T. Intelligent Sustainable Systems. View
  12. Jay A. Transformational Leadership Styles for Global Leaders. View
  13. Lasisi R. Proceedings of the Future Technologies Conference (FTC) 2023, Volume 2. View
  14. Shoenbill K, Kasturi S, Mendonca E. Chronic Illness Care. View
  15. Hoor-Ul-Ain S, Khan A, Siddiqui S, Dey I. Computational Methods in Psychiatry. View
  16. Chahar R, Dubey A, Narang S. Advances in Communication and Applications. View
  17. Garg R, Gupta A. Advances in Data-Driven Computing and Intelligent Systems. View
  18. Daneshvar H, Boursalie O, Samavi R, Doyle T, Duncan L, Pires P, Sassi R. Artificial Intelligence for Medicine. View
  19. Afşin Y, Taşkaya Temizel T. Persuasive Technology. View
  20. Fallah A, Aghdam M. Nonlinear Approaches in Engineering Application. View
  21. Perna G, Alciati A, Nemeroff C. The American Psychiatric Association Publishing Textbook of Psychopharmacology. View
  22. Sotolář O, Plhák J, Šmahel D. Text, Speech, and Dialogue. View
  23. Aggarwal R, Singh G, Aggarwal E. Artificial Intelligence‐Enabled Blockchain Technology and Digital Twin for Smart Hospitals. View
  24. Jerlina I, Uma Maheswari M. Deep Sciences for Computing and Communications. View