Published on in Vol 3, No 1 (2016): Jan-Mar
Journals
- Faurholt-Jepsen M, Bauer M, Kessing L. Smartphone-based objective monitoring in bipolar disorder: status and considerations. International Journal of Bipolar Disorders 2018;6(1) View
- Marshall J, Dunstan D, Bartik W. Clinical or gimmickal: The use and effectiveness of mobile mental health apps for treating anxiety and depression. Australian & New Zealand Journal of Psychiatry 2020;54(1):20 View
- Trifan A, Oliveira M, Oliveira J. Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations. JMIR mHealth and uHealth 2019;7(8):e12649 View
- Faurholt-Jepsen M, Geddes J, Goodwin G, Bauer M, Duffy A, Vedel Kessing L, Saunders K. Reporting guidelines on remotely collected electronic mood data in mood disorder (eMOOD)—recommendations. Translational Psychiatry 2019;9(1) View
- Goodday S, Cipriani A. Challenges in identifying behavioural markers of bipolar disorder through objective smartphone data. Australian & New Zealand Journal of Psychiatry 2019;53(2):168 View
- Reinertsen E, Clifford G. A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. Physiological Measurement 2018;39(5):05TR01 View
- Bauer A, Iles-Shih M, Ghomi R, Rue T, Grover T, Kincler N, Miller M, Katon W. Acceptability of mHealth augmentation of Collaborative Care: A mixed methods pilot study. General Hospital Psychiatry 2018;51:22 View
- Majumder S, Deen M. Smartphone Sensors for Health Monitoring and Diagnosis. Sensors 2019;19(9):2164 View
- Meekan M, Duarte C, Fernández-Gracia J, Thums M, Sequeira A, Harcourt R, Eguíluz V. The Ecology of Human Mobility. Trends in Ecology & Evolution 2017;32(3):198 View
- Van Ameringen M, Turna J, Khalesi Z, Pullia K, Patterson B. There is an app for that! The current state of mobile applications (apps) for DSM-5 obsessive-compulsive disorder, posttraumatic stress disorder, anxiety and mood disorders. Depression and Anxiety 2017;34(6):526 View
- Seppälä J, De Vita I, Jämsä T, Miettunen J, Isohanni M, Rubinstein K, Feldman Y, Grasa E, Corripio I, Berdun J, D'Amico E, Bulgheroni M. Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review. JMIR Mental Health 2019;6(2):e9819 View
- Moran J, Kelly G, Haberlin C, Mockler D, Broderick J. The use of eHealth to promote physical activity in patients with mental health conditions: a systematic review. HRB Open Research 2018;1:5 View
- Dogan E, Sander C, Wagner X, Hegerl U, Kohls E. Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review. Journal of Medical Internet Research 2017;19(7):e262 View
- Mühlbauer E, Bauer M, Ebner-Priemer U, Ritter P, Hill H, Beier F, Kleindienst N, Severus E. Effectiveness of smartphone-based ambulatory assessment (SBAA-BD) including a predicting system for upcoming episodes in the long-term treatment of patients with bipolar disorders: study protocol for a randomized controlled single-blind trial. BMC Psychiatry 2018;18(1) View
- Bourla A, Ferreri F, Ogorzelec L, Guinchard C, Mouchabac S. Évaluation des troubles thymiques par l’étude des données passives : le concept de phénotype digital à l’épreuve de la culture de métier de psychiatre. L'Encéphale 2018;44(2):168 View
- Faurholt-Jepsen M, Busk J, Þórarinsdóttir H, Frost M, Bardram J, Vinberg M, Kessing L. Objective smartphone data as a potential diagnostic marker of bipolar disorder. Australian & New Zealand Journal of Psychiatry 2019;53(2):119 View
- Jungmann S, Klan T, Kuhn S, Jungmann F. Accuracy of a Chatbot (Ada) in the Diagnosis of Mental Disorders: Comparative Case Study With Lay and Expert Users. JMIR Formative Research 2019;3(4):e13863 View
- Quiroz J, Geangu E, Yong M. Emotion Recognition Using Smart Watch Sensor Data: Mixed-Design Study. JMIR Mental Health 2018;5(3):e10153 View
- Bidargaddi N, Musiat P, Makinen V, Ermes M, Schrader G, Licinio J. Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies. Molecular Psychiatry 2017;22(2):164 View
- . Digital Sensory Phenotyping for Psychiatric Disorders. Journal of Psychiatry and Brain Science 2020 View
- Fraccaro P, Beukenhorst A, Sperrin M, Harper S, Palmier-Claus J, Lewis S, Van der Veer S, Peek N. Digital biomarkers from geolocation data in bipolar disorder and schizophrenia: a systematic review. Journal of the American Medical Informatics Association 2019;26(11):1412 View
- Moran J, Kelly G, Haberlin C, Mockler D, Broderick J. The use of eHealth to promote physical activity in people with mental health conditions: a systematic review. HRB Open Research 2018;1:5 View
- Ryan K, Babu P, Easter R, Saunders E, Lee A, Klasnja P, Verchinina L, Micol V, Doil B, McInnis M, Kilbourne A. A Smartphone App to Monitor Mood Symptoms in Bipolar Disorder: Development and Usability Study. JMIR Mental Health 2020;7(9):e19476 View
- Haines-Delmont A, Chahal G, Bruen A, Wall A, Khan C, Sadashiv R, Fearnley D. Testing Suicide Risk Prediction Algorithms Using Phone Measurements With Patients in Acute Mental Health Settings: Feasibility Study. JMIR mHealth and uHealth 2020;8(6):e15901 View
- Rajagopalan A, Shah P, Zhang M, Ho R. Digital Platforms in the Assessment and Monitoring of Patients with Bipolar Disorder. Brain Sciences 2017;7(11):150 View
- Cornet V, Holden R. Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of Biomedical Informatics 2018;77:120 View
- Parker G, Tavella G. Design limitations to bipolar II treatment efficacy studies: A challenge and a revisionist strategy. Journal of Affective Disorders 2018;229:334 View
- Faurholt-Jepsen M, Busk J, Vinberg M, Christensen E, Þórarinsdóttir H, Frost M, Bardram J, Kessing L. Daily mobility patterns in patients with bipolar disorder and healthy individuals. Journal of Affective Disorders 2021;278:413 View
- Saunders K, Bilderbeck A, Panchal P, Atkinson L, Geddes J, Goodwin G. Experiences of Remote Mood and Activity Monitoring in Bipolar Disorder: A Qualitative Study. European Psychiatry 2017;41(1):115 View
- Pennou A, Lecomte T, Potvin S, Khazaal Y. Mobile Intervention for Individuals With Psychosis, Dual Disorders, and Their Common Comorbidities: A Literature Review. Frontiers in Psychiatry 2019;10 View
- Jacobson N, Chung Y. Passive Sensing of Prediction of Moment-To-Moment Depressed Mood among Undergraduates with Clinical Levels of Depression Sample Using Smartphones. Sensors 2020;20(12):3572 View
- Meyer T, Crist N, La Rosa N, Ye B, Soares J, Bauer I. Are existing self‐ratings of acute manic symptoms in adults reliable and valid?—A systematic review. Bipolar Disorders 2020;22(6):558 View
- Owen J, Jaworski B, Kuhn E, Hoffman J, Schievelbein L, Chang A, Ramsey K, Rosen C. Development of a mobile app for family members of Veterans with PTSD: identifying needs and modifiable factors associated with burden, depression, and anxiety. Journal of Family Studies 2020;26(2):286 View
- Rohani D, Faurholt-Jepsen M, Kessing L, Bardram J. Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review. JMIR mHealth and uHealth 2018;6(8):e165 View
- Marshall J, Dunstan D, Bartik W. Effectiveness of Using Mental Health Mobile Apps as Digital Antidepressants for Reducing Anxiety and Depression: Protocol for a Multiple Baseline Across-Individuals Design. JMIR Research Protocols 2020;9(7):e17159 View
- Coelho Y, Bastos-Filho T. A Bipolar Disorder Monitoring System Based on Wearable Device and Smartphone. IFAC-PapersOnLine 2016;49(30):216 View
- Moran J, Kelly G, Haberlin C, Mockler D, Broderick J. The use of eHealth to promote physical activity in people with mental health conditions: a systematic review. HRB Open Research 2018;1:5 View
- Torous J, Rodriguez J, Powell A. The New Digital Divide For Digital Biomarkers. Digital Biomarkers 2017;1(1):87 View
- Knight A, Bidargaddi N. Commonly available activity tracker apps and wearables as a mental health outcome indicator: A prospective observational cohort study among young adults with psychological distress. Journal of Affective Disorders 2018;236:31 View
- Di Matteo D, Fotinos K, Lokuge S, Yu J, Sternat T, Katzman M, Rose J. The Relationship Between Smartphone-Recorded Environmental Audio and Symptomatology of Anxiety and Depression: Exploratory Study. JMIR Formative Research 2020;4(8):e18751 View
- White B, Martin A, White J, Burns S, Maycock B, Giglia R, Scott J. Theory-Based Design and Development of a Socially Connected, Gamified Mobile App for Men About Breastfeeding (Milk Man). JMIR mHealth and uHealth 2016;4(2):e81 View
- Pham Q, Graham G, Carrion C, Morita P, Seto E, Stinson J, Cafazzo J. A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review. JMIR mHealth and uHealth 2019;7(1):e11941 View
- Gillett G, Saunders K. Remote Monitoring for Understanding Mechanisms and Prediction in Psychiatry. Current Behavioral Neuroscience Reports 2019;6(2):51 View
- Park D, Goering E, Head K, Bartlett Ellis R. Implications for Training on Smartphone Medication Reminder App Use by Adults With Chronic Conditions: Pilot Study Applying the Technology Acceptance Model. JMIR Formative Research 2017;1(1):e5 View
- Song K, Lee S, Yoon W, Kim C, Joo Y, Lee J, Chon M. Developing and Clinical Application of a Smartphone Mobile Mood Chart Application in Korean for Patients with Bipolar Disorder. Journal of Korean Neuropsychiatric Association 2018;57(3):244 View
- Moura I, Teles A, Silva F, Viana D, Coutinho L, Barros F, Endler M. Mental health ubiquitous monitoring supported by social situation awareness: A systematic review. Journal of Biomedical Informatics 2020;107:103454 View
- Antosik-Wójcińska A, Dominiak M, Chojnacka M, Kaczmarek-Majer K, Opara K, Radziszewska W, Olwert A, Święcicki Ł. Smartphone as a monitoring tool for bipolar disorder: a systematic review including data analysis, machine learning algorithms and predictive modelling. International Journal of Medical Informatics 2020;138:104131 View
- Wang E, Zhou L, Chen S, Hill K, Parmanto B. An mHealth Platform for Supporting Clinical Data Integration into Augmentative and Alternative Communication Service Delivery: User-Centered Design and Usability Evaluation. JMIR Rehabilitation and Assistive Technologies 2018;5(2):e14 View
- Bruen A, Wall A, Haines-Delmont A, Perkins E. Exploring Suicidal Ideation Using an Innovative Mobile App-Strength Within Me: The Usability and Acceptability of Setting up a Trial Involving Mobile Technology and Mental Health Service Users. JMIR Mental Health 2020;7(9):e18407 View
- Taeger J, Bischoff S, Hagen R, Rak K. Utilization of Smartphone Depth Mapping Cameras for App-Based Grading of Facial Movement Disorders: Development and Feasibility Study. JMIR mHealth and uHealth 2021;9(1):e19346 View
- Liu J, Xu K, Zhu G, Zhang Q, Li X. Effects of smartphone-based interventions and monitoring on bipolar disorder: A systematic review and meta-analysis. World Journal of Psychiatry 2020;10(11):272 View
- Sela Y, Santamaria L, Amichai-Hamburge Y, Leong V. Towards a Personalized Multi-Domain Digital Neurophenotyping Model for the Detection and Treatment of Mood Trajectories. Sensors 2020;20(20):5781 View
- de Moura I, Teles A, Endler M, Coutinho L, da Silva e Silva F. Recognizing Context-Aware Human Sociability Patterns Using Pervasive Monitoring for Supporting Mental Health Professionals. Sensors 2020;21(1):86 View
- Orsolini L, Fiorani M, Volpe U. Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?. International Journal of Molecular Sciences 2020;21(20):7684 View
- Stanislaus S, Vinberg M, Melbye S, Frost M, Busk J, Bardram J, Kessing L, Faurholt-Jepsen M. Smartphone-based activity measurements in patients with newly diagnosed bipolar disorder, unaffected relatives and control individuals. International Journal of Bipolar Disorders 2020;8(1) View
- Moshe I, Terhorst Y, Opoku Asare K, Sander L, Ferreira D, Baumeister H, Mohr D, Pulkki-Råback L. Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data. Frontiers in Psychiatry 2021;12 View
- Pedrelli P, Fedor S, Ghandeharioun A, Howe E, Ionescu D, Bhathena D, Fisher L, Cusin C, Nyer M, Yeung A, Sangermano L, Mischoulon D, Alpert J, Picard R. Monitoring Changes in Depression Severity Using Wearable and Mobile Sensors. Frontiers in Psychiatry 2020;11 View
- Gutierrez L, Rabbani K, Ajayi O, Gebresilassie S, Rafferty J, Castro L, Banos O. Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management. International Journal of Environmental Research and Public Health 2021;18(3):1327 View
- Fiorinelli M, Di Mario S, Surace A, Mattei M, Russo C, Villa G, Dionisi S, Di Simone E, Giannetta N, Di Muzio M. Smartphone distraction during nursing care: Systematic literature review. Applied Nursing Research 2021;58:151405 View
- Krichen M. Anomalies Detection Through Smartphone Sensors: A Review. IEEE Sensors Journal 2021;21(6):7207 View
- Gillett G, McGowan N, Palmius N, Bilderbeck A, Goodwin G, Saunders K. Digital Communication Biomarkers of Mood and Diagnosis in Borderline Personality Disorder, Bipolar Disorder, and Healthy Control Populations. Frontiers in Psychiatry 2021;12 View
- Maharjan S, Poudyal A, van Heerden A, Byanjankar P, Thapa A, Islam C, Kohrt B, Hagaman A. Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability. BMC Medical Informatics and Decision Making 2021;21(1) View
- Hilty D, Armstrong C, Luxton D, Gentry M, Krupinski E. A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions. Journal of Technology in Behavioral Science 2021;6(2):278 View
- Sheikh M, Qassem M, Kyriacou P. Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring. Frontiers in Digital Health 2021;3 View
- Anýž J, Bakštein E, Dally A, Kolenič M, Hlinka J, Hartmannová T, Urbanová K, Correll C, Novák D, Španiel F. Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study. JMIR Mental Health 2021;8(8):e26348 View
- Lekkas D, Jacobson N. Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma. Scientific Reports 2021;11(1) View
- Patoz M, Hidalgo-Mazzei D, Pereira B, Blanc O, de Chazeron I, Murru A, Verdolini N, Pacchiarotti I, Vieta E, Llorca P, Samalin L. Patients’ adherence to smartphone apps in the management of bipolar disorder: a systematic review. International Journal of Bipolar Disorders 2021;9(1) View
- Morton E, Nicholas J, Yang L, Lapadat L, Barnes S, Provencher M, Depp C, Chan M, Kulur R, Michalak E. Evaluating the quality, safety, and functionality of commonly used smartphone apps for bipolar disorder mood and sleep self-management. International Journal of Bipolar Disorders 2022;10(1) View
- Anthes E. Quoi de neuf docteur smartphone ?. Cerveau & Psycho 2017;N° 91(8):44 View
- Young A, Choi A, Cannedy S, Hoffmann L, Levine L, Liang L, Medich M, Oberman R, Olmos-Ochoa T. Passive Mobile Self-tracking of Mental Health by Veterans With Serious Mental Illness: Protocol for a User-Centered Design and Prospective Cohort Study. JMIR Research Protocols 2022;11(8):e39010 View
- Forchuk C, Serrato J, Lizotte D, Mann R, Taylor G, Husni S. Developing a Smart Home Technology Innovation for People With Physical and Mental Health Problems: Considerations and Recommendations. JMIR mHealth and uHealth 2022;10(4):e25116 View
- Miller M, Raugh I, Strauss G, Harvey P. Remote digital phenotyping in serious mental illness: Focus on negative symptoms, mood symptoms, and self-awareness. Biomarkers in Neuropsychiatry 2022;6:100047 View
- Gopalakrishnan A, Venkataraman R, Gururajan R, Zhou X, Genrich R. Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review. PeerJ Computer Science 2022;8:e1042 View
- Sargazi S, Zahedi Abghari A, Mirinejad S, Heidari Nia M, Majidpour M, Danesh H, Saravani R, Sheervalilou R, Shakiba M, Zahedi Abghari F. Long noncoding RNA HOTAIR polymorphisms and susceptibility to bipolar disorder: a preliminary case–control study. Nucleosides, Nucleotides & Nucleic Acids 2022;41(7):684 View
- Mullick T, Radovic A, Shaaban S, Doryab A. Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study. JMIR Formative Research 2022;6(6):e35807 View
- Dominiak M, Kaczmarek-Majer K, Antosik-Wójcińska A, Opara K, Olwert A, Radziszewska W, Hryniewicz O, Święcicki Ł, Wojnar M, Mierzejewski P. Behavioral and Self-reported Data Collected From Smartphones for the Assessment of Depressive and Manic Symptoms in Patients With Bipolar Disorder: Prospective Observational Study. Journal of Medical Internet Research 2022;24(1):e28647 View
- Melbye S, Stanislaus S, Vinberg M, Frost M, Bardram J, Kessing L, Faurholt-Jepsen M. Automatically Generated Smartphone Data in Young Patients With Newly Diagnosed Bipolar Disorder and Healthy Controls. Frontiers in Psychiatry 2021;12 View
- Sangha N, Lyall L, Wyse C, Cullen B, Whalley H, Smith D. The nosological status of unipolar mania and hypomania within UK Biobank according to objective and subjective measures of diurnal rest and activity. Bipolar Disorders 2022;24(7):726 View
- Tatham I, Clarke E, Grieve K, Kaushal P, Smeddinck J, Millar E, Sharma A. Process and Outcome Evaluations of Smartphone Apps for Bipolar Disorder: Scoping Review. Journal of Medical Internet Research 2022;24(3):e29114 View
- Jameel L, Valmaggia L, Barnes G, Cella M. mHealth technology to assess, monitor and treat daily functioning difficulties in people with severe mental illness: A systematic review. Journal of Psychiatric Research 2022;145:35 View
- Braund T, Zin M, Boonstra T, Wong Q, Larsen M, Christensen H, Tillman G, O’Dea B. Smartphone Sensor Data for Identifying and Monitoring Symptoms of Mood Disorders: A Longitudinal Observational Study. JMIR Mental Health 2022;9(5):e35549 View
- Ross M, Tulabandhula T, Bennett C, Baek E, Kim D, Hussain F, Demos A, Ning E, Langenecker S, Ajilore O, Leow A. A Novel Approach to Clustering Accelerometer Data for Application in Passive Predictions of Changes in Depression Severity. Sensors 2023;23(3):1585 View
- Fletcher K, Lindblom K, Seabrook E, Foley F, Murray G. Pilot Testing in the Wild: Feasibility, Acceptability, Usage Patterns, and Efficacy of an Integrated Web and Smartphone Platform for Bipolar II Disorder. JMIR Formative Research 2022;6(5):e32740 View
- Sarni N. Nouvelles influences pour la nosographie psychiatrique. Annales Médico-psychologiques, revue psychiatrique 2022;180(1):85 View
- White K, Williamson C, Bergou N, Oetzmann C, de Angel V, Matcham F, Henderson C, Hotopf M. A systematic review of engagement reporting in remote measurement studies for health symptom tracking. npj Digital Medicine 2022;5(1) View
- Anmella G, Faurholt‐Jepsen M, Hidalgo‐Mazzei D, Radua J, Passos I, Kapczinski F, Minuzzi L, Alda M, Meier S, Hajek T, Ballester P, Birmaher B, Hafeman D, Goldstein T, Brietzke E, Duffy A, Haarman B, López‐Jaramillo C, Yatham L, Lam R, Isometsa E, Mansur R, McIntyre R, Mwangi B, Vieta E, Kessing L. Smartphone‐based interventions in bipolar disorder: Systematic review and meta‐analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force. Bipolar Disorders 2022;24(6):580 View
- Svensson M, Erhardt S, Hållmarker U, James S, Deierborg T. A physically active lifestyle is associated with lower long-term incidence of bipolar disorder in a population-based, large-scale study. International Journal of Bipolar Disorders 2022;10(1) View
- Bjella T, Collier Høegh M, Holmstul Olsen S, Aminoff S, Barrett E, Ueland T, Icick R, Andreassen O, Nerhus M, Myhre Ihler H, Hagen M, Busch-Christensen C, Melle I, Lagerberg T. Developing “MinDag” – an app to capture symptom variation and illness mechanisms in bipolar disorder. Frontiers in Medical Technology 2022;4 View
- Abdullah S, Choudhury T. Sensing Technologies for Monitoring Serious Mental Illnesses. IEEE MultiMedia 2018;25(1):61 View
- Tsai C, Chen P, Liu D, Kuo Y, Hsieh T, Chiang D, Lai F, Wu C. Panic Attack Prediction Using Wearable Devices and Machine Learning: Development and Cohort Study. JMIR Medical Informatics 2022;10(2):e33063 View
- Torous J, Bucci S, Bell I, Kessing L, Faurholt‐Jepsen M, Whelan P, Carvalho A, Keshavan M, Linardon J, Firth J. The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry 2021;20(3):318 View
- Vega J, Li M, Aguillera K, Goel N, Joshi E, Khandekar K, Durica K, Kunta A, Low C. Reproducible Analysis Pipeline for Data Streams: Open-Source Software to Process Data Collected With Mobile Devices. Frontiers in Digital Health 2021;3 View
- Vega J, Bell B, Taylor C, Xie J, Ng H, Honary M, McNaney R. Detecting Mental Health Behaviors Using Mobile Interactions: Exploratory Study Focusing on Binge Eating. JMIR Mental Health 2022;9(4):e32146 View
- Ortiz A, Maslej M, Husain M, Daskalakis Z, Mulsant B. Apps and gaps in bipolar disorder: A systematic review on electronic monitoring for episode prediction. Journal of Affective Disorders 2021;295:1190 View
- Hoel S, Victory A, Sagorac Gruichich T, Stowe Z, McInnis M, Cochran A, Thomas E. A Mixed-Methods Analysis of Mobile ACT Responses From Two Cohorts. Frontiers in Digital Health 2022;4 View
- Arya S, Dias S, Jelinek H, Hadjileontiadis L, Pappa A. The convergence of traditional and digital biomarkers through AI-assisted biosensing: A new era in translational diagnostics?. Biosensors and Bioelectronics 2023;235:115387 View
- Nash C, Nair R, Naqvi S. Machine Learning in ADHD and Depression Mental Health Diagnosis: A Survey. IEEE Access 2023;11:86297 View
- Kadirvelu B, Bellido Bel T, Wu X, Burmester V, Ananth S, Cabral C C Branco B, Girela-Serrano B, Gledhill J, Di Simplicio M, Nicholls D, Faisal A. Mindcraft, a Mobile Mental Health Monitoring Platform for Children and Young People: Development and Acceptability Pilot Study. JMIR Formative Research 2023;7:e44877 View
- Medich M, Cannedy S, Hoffmann L, Chinchilla M, Pila J, Chassman S, Calderon R, Young A. Clinician and Patient Perspectives on the Use of Passive Mobile Monitoring and Self-Tracking for Patients With Serious Mental Illness: User-Centered Approach. JMIR Human Factors 2023;10:e46909 View
- Shin J, Bae S. A Systematic Review of Location Data for Depression Prediction. International Journal of Environmental Research and Public Health 2023;20(11):5984 View
- Caratù M, Pigliautile I, Piselli C, Fabiani C. A perspective on managing cities and citizens' well-being through smart sensing data. Environmental Science & Policy 2023;147:169 View
- Heydarian S, Shakiba A, Rostam Niakan Kalhori S. The Minimum Feature Set for Designing Mobile Apps to Support Bipolar Disorder-Affected Patients: Proposal of Essential Functions and Requirements. Journal of Healthcare Informatics Research 2023;7(2):254 View
- Stamatis C, Meyerhoff J, Meng Y, Lin Z, Cho Y, Liu T, Karr C, Liu T, Curtis B, Ungar L, Mohr D. Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study. npj Mental Health Research 2024;3(1) View
- Hsu J, Wu C, Lin E, Chen P. MoodSensing: A smartphone app for digital phenotyping and assessment of bipolar disorder. Psychiatry Research 2024;334:115790 View
- Halabi R, Mulsant B, Alda M, DeShaw A, Hintze A, Husain M, O'Donovan C, Patterson R, Ortiz A. Not missing at random: Missing data are associated with clinical status and trajectories in an electronic monitoring longitudinal study of bipolar disorder. Journal of Psychiatric Research 2024;174:326 View
- Castro M, Zavod M, Rutgersson A, Jörntén-Karlsson M, Dutta B, Hagger L. iPREDICT: Characterization of Asthma Triggers and Selection of Digital Technology to Predict Changes in Disease Control. Journal of Asthma and Allergy 2024;Volume 17:653 View
- Bidargaddi N, Leibbrandt R, Paget T, Verjans J, Looi J, Lipschitz J. Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research. DIGITAL HEALTH 2024;10 View
- Castro M, Zavod M, Rutgersson A, Jörntén-Karlsson M, Dutta B, Hagger L. iPREDICT: proof-of-concept study to develop a predictive model of changes in asthma control. Therapeutic Advances in Respiratory Disease 2024;18 View
- Shvetcov A, Funke Kupper J, Zheng W, Slade A, Han J, Whitton A, Spoelma M, Hoon L, Mouzakis K, Vasa R, Gupta S, Venkatesh S, Newby J, Christensen H. Passive sensing data predicts stress in university students: a supervised machine learning method for digital phenotyping. Frontiers in Psychiatry 2024;15 View
- Hsu J, Wu C, Wang W, Su H, Lin E, Chen P. Digital Phenotyping-Based Bipolar Disorder Assessment Using Multiple Correlation Data Imputation and Lasso-MLP. IEEE Transactions on Affective Computing 2024;15(3):885 View
- Lee T, Chen C, Chen I, Chen H, Wu S, Liu C, Hsiao C, Kuo P. Dynamic bidirectional associations between GPS mobility and ecological momentary assessment of mood symptoms in mood disorders (Preprint). Journal of Medical Internet Research 2023 View
Books/Policy Documents
- Senders J, Maher N, Hulsbergen A, Lamba N, Bredenoord A, Broekman M. Ethics of Innovation in Neurosurgery. View
- Hegerl U, Dogan E, Oehler C, Sander C, Stöber F. Gesundheit digital. View
- Teles A, Barros F, Rodrigues I, Barbosa A, Silva F, Coutinho L, Teixeira S. IoT and ICT for Healthcare Applications. View
- Rajagopalan A, Ho R. Major Depressive Disorder. View
- Tushar A, Kabir M, Ahmed S. Signal Processing Techniques for Computational Health Informatics. View
- Rosenfeld A, Benrimoh D, Armstrong C, Mirchi N, Langlois-Therrien T, Rollins C, Tanguay-Sela M, Mehltretter J, Fratila R, Israel S, Snook E, Perlman K, Kleinerman A, Saab B, Thoburn M, Gabbay C, Yaniv-Rosenfeld A. Applications of Big Data in Healthcare. View
- Mao S, Khalifa Y, Zhang Z, Shu K, Suri A, Bouzid Z, Sejdic E. Digital Health. View
- Anmella G, Hidalgo-Mazzei D, Vieta E. Digital Mental Health. View
- Volpe U, Elkholy H, Gargot T, Pinto da Costa M, Orsolini L. Tasman’s Psychiatry. View
- Devi D, Naresh R, Kumar C, Senthilkumar S, Jovin A. Technological Tools for Predicting Pregnancy Complications. View
- Emmert K, Maetzler W. Gerontechnology. A Clinical Perspective. View
- Volpe U, Elkholy H, Gargot T, Pinto da Costa M, Orsolini L. Tasman’s Psychiatry. View