Published on in Vol 5, No 2 (2017): February

Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia

Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia

Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia

Journals

  1. Gognieva D, Shchekochikhin D, Gavrilova E, Syrkina E, Bogdanova R, Syrkin A, Kopylov P. The problem of adherence to treatment in general medical practice. Kardiologiya i serdechno-sosudistaya khirurgiya 2019;12(6):510 View
  2. Velligan D, Maples N, Pokorny J, Wright C. Assessment of adherence to oral antipsychotic medications: What has changed over the past decade?. Schizophrenia Research 2020;215:17 View
  3. Woo M. An AI boost for clinical trials. Nature 2019;573(7775):S100 View
  4. Dahne J, Tomko R, McClure E, Obeid J, Carpenter M. Remote Methods for Conducting Tobacco-Focused Clinical Trials. Nicotine & Tobacco Research 2020;22(12):2134 View
  5. Gandhi M, Bacchetti P, Spinelli M, Okochi H, Baeten J, Siriprakaisil O, Klinbuayaem V, Rodrigues W, Wang G, Vincent M, Cressey T, Drain P. Brief Report: Validation of a Urine Tenofovir Immunoassay for Adherence Monitoring to PrEP and ART and Establishing the Cutoff for a Point-of-Care Test. JAIDS Journal of Acquired Immune Deficiency Syndromes 2019;81(1):72 View
  6. Fogel A, Kvedar J. Artificial intelligence powers digital medicine. npj Digital Medicine 2018;1(1) View
  7. McCaul M, Wand G. Detecting Deception in Our Research Participants: Are Your Participants Who You Think They Are?. Alcoholism: Clinical and Experimental Research 2018;42(2):230 View
  8. Krittanawong C, Bomback A, Baber U, Bangalore S, Messerli F, Wilson Tang W. Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension. Current Hypertension Reports 2018;20(9) View
  9. Fiske A, Henningsen P, Buyx A. Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy. Journal of Medical Internet Research 2019;21(5):e13216 View
  10. Barrett M, Boyne J, Brandts J, Brunner-La Rocca H, De Maesschalck L, De Wit K, Dixon L, Eurlings C, Fitzsimons D, Golubnitschaja O, Hageman A, Heemskerk F, Hintzen A, Helms T, Hill L, Hoedemakers T, Marx N, McDonald K, Mertens M, Müller-Wieland D, Palant A, Piesk J, Pomazanskyi A, Ramaekers J, Ruff P, Schütt K, Shekhawat Y, Ski C, Thompson D, Tsirkin A, van der Mierden K, Watson C, Zippel-Schultz B. Artificial intelligence supported patient self-care in chronic heart failure: a paradigm shift from reactive to predictive, preventive and personalised care. EPMA Journal 2019;10(4):445 View
  11. Herrmann M, Boehme P, Hansen A, Jansson K, Rebacz P, Ehlers J, Mondritzki T, Truebel H. Digital Competencies and Attitudes Toward Digital Adherence Solutions Among Elderly Patients Treated With Novel Anticoagulants: Qualitative Study. Journal of Medical Internet Research 2020;22(1):e13077 View
  12. Van Biesen W, Decruyenaere J, Sideri K, Cockbain J, Sterckx S. Remote digital monitoring of medication intake: methodological, medical, ethical and legal reflections. Acta Clinica Belgica 2021;76(3):209 View
  13. Mak K, Pichika M. Artificial intelligence in drug development: present status and future prospects. Drug Discovery Today 2019;24(3):773 View
  14. Boehme P, Wienand P, Herrmann M, Truebel H, Mondritzki T. New digital adherence devices could prevent millions of strokes from atrial fibrillation by the end of the next century. Medical Hypotheses 2017;108:46 View
  15. Steinkamp J, Goldblatt N, Borodovsky J, LaVertu A, Kronish I, Marsch L, Schuman-Olivier Z. Technological Interventions for Medication Adherence in Adult Mental Health and Substance Use Disorders: A Systematic Review. JMIR Mental Health 2019;6(3):e12493 View
  16. Eggerth A, Hayn D, Schreier G. Medication management needs information and communications technology‐based approaches, including telehealth and artificial intelligence. British Journal of Clinical Pharmacology 2020;86(10):2000 View
  17. Graham S, Depp C, Lee E, Nebeker C, Tu X, Kim H, Jeste D. Artificial Intelligence for Mental Health and Mental Illnesses: an Overview. Current Psychiatry Reports 2019;21(11) View
  18. Koesmahargyo V, Abbas A, Zhang L, Guan L, Feng S, Yadav V, Galatzer-Levy I. Accuracy of machine learning-based prediction of medication adherence in clinical research. Psychiatry Research 2020;294:113558 View
  19. Vatansever S, Schlessinger A, Wacker D, Kaniskan H, Jin J, Zhou M, Zhang B. Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions. Medicinal Research Reviews 2021;41(3):1427 View
  20. Väänänen A, Haataja K, Vehviläinen-Julkunen K, Toivanen P. AI in healthcare: A narrative review. F1000Research 2021;10:6 View
  21. Aggarwal N, Ahmed M, Basu S, Curtin J, Evans B, Matheny M, Nundy S, Sendak M, Shachar C, Shah R, Thadaney-Israni S. Advancing Artificial Intelligence in Health Settings Outside the Hospital and Clinic. NAM Perspectives 2020 View
  22. Dockendorf M, Hansen B, Bateman K, Moyer M, Shah J, Shipley L. Digitally Enabled, Patient‐Centric Clinical Trials: Shifting the Drug Development Paradigm. Clinical and Translational Science 2021;14(2):445 View
  23. Liu A, Laborde N, Coleman K, Vittinghoff E, Gonzalez R, Wilde G, Thorne A, Ikeguchi E, Shafner L, Sunshine L, van der Straten A, Siegler A, Buchbinder S. DOT Diary: Developing a Novel Mobile App Using Artificial Intelligence and an Electronic Sexual Diary to Measure and Support PrEP Adherence Among Young Men Who Have Sex with Men. AIDS and Behavior 2021;25(4):1001 View
  24. Katz N. Design and conduct of confirmatory chronic pain clinical trials. PAIN Reports 2021;6(1):e845 View
  25. Devine E, Pingitore A, Margiotta K, Hadaway N, Reid K, Peebles K, Hyun J. Frequency of concealment, fabrication and falsification of study data by deceptive subjects. Contemporary Clinical Trials Communications 2021;21:100713 View
  26. Curto M, Fazio F, Ulivieri M, Navari S, Lionetto L, Baldessarini R. Improving adherence to pharmacological treatment for schizophrenia: a systematic assessment. Expert Opinion on Pharmacotherapy 2021;22(9):1143 View
  27. Chivilgina O, Elger B, Jotterand F. Digital Technologies for Schizophrenia Management: A Descriptive Review. Science and Engineering Ethics 2021;27(2) View
  28. Larsen K, Areberg J, Åström D. Are self-reported and self-monitored adherence good proxies for reaching relevant plasma concentrations?: Experiences from a study of anti-depressants in healthy volunteers. Clinical Trials 2021;18(4):505 View
  29. Christie R, Abbas A, Koesmahargyo V, Mirelman A, Dorsey E, Brundin P, Bloem B. Technology for Measuring and Monitoring Treatment Compliance Remotely. Journal of Parkinson's Disease 2021;11(s1):S77 View
  30. Babel A, Taneja R, Mondello Malvestiti F, Monaco A, Donde S. Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases. Frontiers in Digital Health 2021;3 View
  31. Schuhmacher A, Brieke C, Gassmann O, Hinder M, Hartl D. Systematic risk identification and assessment using a new risk map in pharmaceutical R&D. Drug Discovery Today 2021;26(12):2786 View
  32. Salcedo J, Rosales M, Kim J, Nuno D, Suen S, Chang A, Durand-Zaleski I. Cost-effectiveness of artificial intelligence monitoring for active tuberculosis treatment: A modeling study. PLOS ONE 2021;16(7):e0254950 View
  33. Weissler E, Naumann T, Andersson T, Ranganath R, Elemento O, Luo Y, Freitag D, Benoit J, Hughes M, Khan F, Slater P, Shameer K, Roe M, Hutchison E, Kollins S, Broedl U, Meng Z, Wong J, Curtis L, Huang E, Ghassemi M. The role of machine learning in clinical research: transforming the future of evidence generation. Trials 2021;22(1) View
  34. Bijral R, Singh I, Manhas J, Sharma V. Exploring Artificial Intelligence in Drug Discovery: A Comprehensive Review. Archives of Computational Methods in Engineering 2022;29(4):2513 View
  35. Siripurapu S, Darimireddy N, Chehri A, Sridhar B, Paramkusam A. Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-I (AI, Big Data, Block Chain, Open-Source Technologies, and Cloud Computing). Electronics 2023;12(3):750 View
  36. Walton K, Herrmann E. Medication adherence in tobacco cessation clinical trials. Addiction Neuroscience 2023;6:100069 View
  37. Väänänen A, Haataja K, Vehviläinen-Julkunen K, Toivanen P. AI in healthcare: A narrative review. F1000Research 2021;10:6 View
  38. Kwon S, Firth J, Joshi D, Torous J. Accessibility and availability of smartphone apps for schizophrenia. Schizophrenia 2022;8(1) View
  39. Correll C, Solmi M, Cortese S, Fava M, Højlund M, Kraemer H, McIntyre R, Pine D, Schneider L, Kane J. The future of psychopharmacology: a critical appraisal of ongoing phase 2/3 trials, and of some current trends aiming to de‐risk trial programmes of novel agents. World Psychiatry 2023;22(1):48 View
  40. Ray A, Bhardwaj A, Malik Y, Singh S, Gupta R. Artificial intelligence and Psychiatry: An overview. Asian Journal of Psychiatry 2022;70:103021 View
  41. Khan N, Javed M. Use of Artificial Intelligence-Based Strategies for Assessing Suicidal Behavior and Mental Illness: A Literature Review. Cureus 2022 View
  42. Mason M, Cho Y, Rayo J, Gong Y, Harris M, Jiang Y. Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review. JMIR mHealth and uHealth 2022;10(3):e35157 View
  43. Schmidt A, Balitzki J, Grmaca L, Vogel J, Boehme P, Boden K, Hüser J, Truebel H, Mondritzki T. “Digital biomarkers” in preclinical heart failure models — a further step towards improved translational research. Heart Failure Reviews 2022;28(1):249 View
  44. Krittanawong C, Johnson K, Tang W. How Artificial Intelligence Could Redefine Clinical Trials in Cardiovascular Medicine: Lessons Learned from Oncology. Personalized Medicine 2019;16(2):87 View
  45. Adje Y, Brooks K, Castillo-Mancilla J, Wyles D, Anderson P, Kiser J. The use of technology-based adherence monitoring in the treatment of hepatitis C virus. Therapeutic Advances in Infectious Disease 2022;9:204993612210956 View
  46. Goodman G, Vaz C, Albrechta H, Boyer E, Mayer K, O’Cleirigh C, Chai P. Ingestible Electronic Sensors for Monitoring Real-time Adherence to HIV Pre-exposure Prophylaxis and Antiretroviral Therapy. Current HIV/AIDS Reports 2022;19(5):433 View
  47. Bohlmann A, Mostafa J, Kumar M. Machine Learning and Medication Adherence: Scoping Review. JMIRx Med 2021;2(4):e26993 View
  48. Correia F, Molinos M, Luís S, Carvalho D, Carvalho C, Costa P, Seabra R, Francisco G, Bento V, Lains J. Digitally Assisted Versus Conventional Home-Based Rehabilitation After Arthroscopic Rotator Cuff Repair. American Journal of Physical Medicine & Rehabilitation 2022;101(3):237 View
  49. Buchbinder S, Siegler A, Coleman K, Vittinghoff E, Wilde G, Lockard A, Scott H, Anderson P, Laborde N, van der Straten A, Christie R, Marlborough M, Liu A. Randomized Controlled Trial of Automated Directly Observed Therapy for Measurement and Support of PrEP Adherence Among Young Men Who have Sex with Men. AIDS and Behavior 2023;27(2):719 View
  50. Tiribelli S, Monnot A, Shah S, Arora A, Toong P, Kong S. Ethics Principles for Artificial Intelligence–Based Telemedicine for Public Health. American Journal of Public Health 2023;113(5):577 View
  51. Jung J. Current Status and Future Direction of Artificial Intelligence in Healthcare and Medical Education. Korean Medical Education Review 2020;22(2):99 View
  52. Lu M, Yin J, Zhu Q, Lin G, Mou M, Liu F, Pan Z, You N, Lian X, Li F, Zhang H, Zheng L, Zhang W, Zhang H, Shen Z, Gu Z, Li H, Zhu F. Artificial Intelligence in Pharmaceutical Sciences. Engineering 2023;27:37 View
  53. McIntyre R, Greenleaf W, Bulaj G, Taylor S, Mitsi G, Saliu D, Czysz A, Silvesti G, Garcia M, Jain R. Digital health technologies and major depressive disorder. CNS Spectrums 2023;28(6):662 View
  54. Chakraborty C, Bhattacharya M, Dhama K, Agoramoorthy G. Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period. International Journal of Surgery 2023;109(5):1535 View
  55. Malik M, Faraone S, Michoel T, Haavik J. Use of big data and machine learning algorithms to extract possible treatment targets in neurodevelopmental disorders. Pharmacology & Therapeutics 2023;250:108530 View
  56. Habeeba S. Use of Artificial Intelligence in Drug Discovery and its Application in Drug Development. Asian Journal of Research in Chemistry 2023:83 View
  57. Ekpezu A, Wiafe I, Oinas-Kukkonen H. Predicting Adherence to Behavior Change Support Systems using Machine Learning: A Systematic Review (Preprint). JMIR AI 2023 View
  58. Peng W, Bai X, Yang Y, Cui J, Xu W, Song L, Yang H, He W, Zhang Y, Zhang X, Li X, Lu J. Healthy lifestyle, statin, and mortality in people with high CVD risk: A nationwide population-based cohort study. American Journal of Preventive Cardiology 2024;17:100635 View
  59. 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
  60. Nazarzadeh M. Polypill: a harmonious blend of stoicism and pragmatism in primary cardiovascular prevention. Heart 2024:heartjnl-2024-323953 View
  61. Salave S, Rana D, Benival D, Jain A. Decoding Artificial Intelligence in Neuroscience: Applications Beyond Diagnosis. Current Indian Science 2023;01 View
  62. Kwok W, Zhang Y, Wang G. Artificial intelligence in perinatal mental health research: A scoping review. Computers in Biology and Medicine 2024;177:108685 View
  63. Stoner M, Maragh-Bass A, Sukhija-Cohen A, Saberi P. Digital directly observed therapy to monitor adherence to medications: a scoping review. HIV Research & Clinical Practice 2022;23(1):47 View

Books/Policy Documents

  1. Lu P, Yang Y, Liu S, Xie L, Lure F, Li M. Tuberculosis Control in Migrating Population. View
  2. De Geest S, Ribaut J, Denhaerynck K, Dobbels F. Psychosocial Aspects of Chronic Kidney Disease. View
  3. Santoshi S, Sengupta D. Artificial Intelligence and Machine Learning in Healthcare. View
  4. Schneider H. Artificial Intelligence in Medicine. View
  5. Schneider H. Artificial Intelligence in Medicine. View
  6. Chavda V, Vihol D, Patel A, Redwan E, Uversky V. Bioinformatics Tools for Pharmaceutical Drug Product Development. View
  7. Saikia S, Prajapati J, Prajapati B, Padma V, Pathak Y. Recent Advances in Therapeutic Drug Monitoring and Clinical Toxicology. View
  8. Pokhriyal P, Chavda V, Pathak M. Bioinformatics Tools for Pharmaceutical Drug Product Development. View
  9. Naeem A, Suhail M, Basit A, Yali L, Xia Z, Qin Z, Ming Y. A Handbook of Artificial Intelligence in Drug Delivery. View
  10. Argenson A, Devi-Chou V. Principles of Gender-Specific Medicine. View
  11. Nag A, Das A, Sil R, Kar A, Mandal D, Das B. Intelligent Systems Design and Applications. View
  12. Das D, Satpathy I, Patnaik B. AI and IoT-Based Technologies for Precision Medicine. View
  13. Mancini A, Fabbo A. Noninvasive Mechanical Ventilation and Neuropsychiatric Disorders. View
  14. Fielding K, Subbaraman R, Khan A, Celan C, Charalambous S, Franke M, Huddart S, Katamba A, Law S, Stagg H. Digital Respiratory Healthcare. View
  15. Mourelatou E, Iosif E, Galatou E, Sarigiannis Y, Vlasiou M, Zacharia L, Petrou C. Novel Formulations and Future Trends. View
  16. Qian S, Yang Y. HCI International 2024 Posters. View