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 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

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