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For: Bain EE, Shafner L, Walling DP, Othman AA, Chuang-Stein C, Hinkle J, Hanina A. Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia. JMIR Mhealth Uhealth 2017;5:e18. [PMID: 28223265 DOI: 10.2196/mhealth.7030] [Cited by in Crossref: 43] [Cited by in F6Publishing: 33] [Article Influence: 8.6] [Reference Citation Analysis]
Number Citing Articles
1 Dahne J, Tomko RL, McClure EA, Obeid JS, Carpenter MJ. Remote Methods for Conducting Tobacco-Focused Clinical Trials. Nicotine Tob Res 2020;22:2134-40. [PMID: 32531046 DOI: 10.1093/ntr/ntaa105] [Cited by in Crossref: 12] [Cited by in F6Publishing: 11] [Article Influence: 6.0] [Reference Citation Analysis]
2 Litwin AH, Shafner L, Norton B, Akiyama MJ, Agyemang L, Guzman M, Vera T, Heo M. Artificial Intelligence Platform Demonstrates High Adherence in Patients Receiving Fixed-Dose Ledipasvir and Sofosbuvir: A Pilot Study. Open Forum Infect Dis 2020;7:ofaa290. [PMID: 32818140 DOI: 10.1093/ofid/ofaa290] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
3 Katz N. Design and conduct of confirmatory chronic pain clinical trials. Pain Rep 2021;6:e845. [PMID: 33511323 DOI: 10.1097/PR9.0000000000000854] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Steinkamp JM, Goldblatt N, Borodovsky JT, LaVertu A, Kronish IM, Marsch LA, Schuman-Olivier Z. Technological Interventions for Medication Adherence in Adult Mental Health and Substance Use Disorders: A Systematic Review. JMIR Ment Health 2019;6:e12493. [PMID: 30860493 DOI: 10.2196/12493] [Cited by in Crossref: 32] [Cited by in F6Publishing: 24] [Article Influence: 10.7] [Reference Citation Analysis]
5 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 Discov Today 2021:S1359-6446(21)00287-7. [PMID: 34229082 DOI: 10.1016/j.drudis.2021.06.015] [Reference Citation Analysis]
6 Larsen KG, Areberg J, Åström DO. Are self-reported and self-monitored adherence good proxies for reaching relevant plasma concentrations?: Experiences from a study of anti-depressants in healthy volunteers. Clin Trials 2021;18:505-10. [PMID: 33938259 DOI: 10.1177/17407745211012683] [Reference Citation Analysis]
7 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. Med Hypotheses 2017;108:46-50. [PMID: 29055399 DOI: 10.1016/j.mehy.2017.07.034] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
8 Christie RH, Abbas A, Koesmahargyo V. Technology for Measuring and Monitoring Treatment Compliance Remotely. J Parkinsons Dis 2021;11:S77-81. [PMID: 34151856 DOI: 10.3233/JPD-212537] [Reference Citation Analysis]
9 Graham S, Depp C, Lee EE, Nebeker C, Tu X, Kim HC, Jeste DV. Artificial Intelligence for Mental Health and Mental Illnesses: an Overview. Curr Psychiatry Rep 2019;21:116. [PMID: 31701320 DOI: 10.1007/s11920-019-1094-0] [Cited by in Crossref: 48] [Cited by in F6Publishing: 29] [Article Influence: 16.0] [Reference Citation Analysis]
10 Herrmann M, Boehme P, Hansen A, Jansson K, Rebacz P, Ehlers JP, Mondritzki T, Truebel H. Digital Competencies and Attitudes Toward Digital Adherence Solutions Among Elderly Patients Treated With Novel Anticoagulants: Qualitative Study. J Med Internet Res 2020;22:e13077. [PMID: 32012049 DOI: 10.2196/13077] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
11 Mak KK, Pichika MR. Artificial intelligence in drug development: present status and future prospects. Drug Discov Today 2019;24:773-80. [PMID: 30472429 DOI: 10.1016/j.drudis.2018.11.014] [Cited by in Crossref: 133] [Cited by in F6Publishing: 84] [Article Influence: 33.3] [Reference Citation Analysis]
12 Barrett M, Boyne J, Brandts J, Brunner-La Rocca HP, De Maesschalck L, De Wit K, Dixon L, Eurlings C, Fitzsimons D, Golubnitschaja O, Hageman A, Heemskerk F, Hintzen A, Helms TM, 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 CF, Thompson DR, 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 J 2019;10:445-64. [PMID: 31832118 DOI: 10.1007/s13167-019-00188-9] [Cited by in Crossref: 28] [Cited by in F6Publishing: 21] [Article Influence: 9.3] [Reference Citation Analysis]
13 Liu AY, Laborde ND, Coleman K, Vittinghoff E, Gonzalez R, Wilde G, Thorne AL, Ikeguchi E, Shafner L, Sunshine L, van der Straten A, Siegler AJ, 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 Behav 2021;25:1001-12. [PMID: 33044687 DOI: 10.1007/s10461-020-03054-2] [Cited by in Crossref: 14] [Cited by in F6Publishing: 10] [Article Influence: 14.0] [Reference Citation Analysis]
14 McCaul ME, Wand GS. Detecting Deception in Our Research Participants: Are Your Participants Who You Think They Are? Alcohol Clin Exp Res 2018;42:230-7. [PMID: 29286543 DOI: 10.1111/acer.13556] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
15 Eggerth A, Hayn D, Schreier G. Medication management needs information and communications technology-based approaches, including telehealth and artificial intelligence. Br J Clin Pharmacol 2020;86:2000-7. [PMID: 31271668 DOI: 10.1111/bcp.14045] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 2.3] [Reference Citation Analysis]
16 Krittanawong C, Bomback AS, Baber U, Bangalore S, Messerli FH, Wilson Tang WH. Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension. Curr Hypertens Rep 2018;20:75. [PMID: 29980865 DOI: 10.1007/s11906-018-0875-x] [Cited by in Crossref: 26] [Cited by in F6Publishing: 15] [Article Influence: 6.5] [Reference Citation Analysis]
17 Curto M, Fazio F, Ulivieri M, Navari S, Lionetto L, Baldessarini RJ. Improving adherence to pharmacological treatment for schizophrenia: a systematic assessment. Expert Opin Pharmacother 2021;22:1143-55. [PMID: 33543659 DOI: 10.1080/14656566.2021.1882996] [Reference Citation Analysis]
18 Aggarwal N, Ahmed M, Basu S, Curtin JJ, Evans BJ, Matheny ME, Nundy S, Sendak MP, Shachar C, Shah RU, Thadaney-israni S. Advancing Artificial Intelligence in Health Settings Outside the Hospital and Clinic. NAM Perspectives. [DOI: 10.31478/202011f] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
19 Fogel AL, Kvedar JC. Artificial intelligence powers digital medicine. NPJ Digit Med 2018;1:5. [PMID: 31304291 DOI: 10.1038/s41746-017-0012-2] [Cited by in Crossref: 106] [Cited by in F6Publishing: 63] [Article Influence: 26.5] [Reference Citation Analysis]
20 Bijral RK, Singh I, Manhas J, Sharma V. Exploring Artificial Intelligence in Drug Discovery: A Comprehensive Review. Arch Computat Methods Eng. [DOI: 10.1007/s11831-021-09661-z] [Reference Citation Analysis]
21 Devine EG, Pingitore AM, Margiotta KN, Hadaway NA, Reid K, Peebles K, Hyun JW. Frequency of concealment, fabrication and falsification of study data by deceptive subjects. Contemp Clin Trials Commun 2021;21:100713. [PMID: 33604482 DOI: 10.1016/j.conctc.2021.100713] [Reference Citation Analysis]
22 Vatansever S, Schlessinger A, Wacker D, Kaniskan HÜ, Jin J, Zhou MM, Zhang B. Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions. Med Res Rev 2021;41:1427-73. [PMID: 33295676 DOI: 10.1002/med.21764] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
23 Väänänen A, Haataja K, Vehviläinen-julkunen K, Toivanen P. AI in healthcare: A narrative review. F1000Res 2021;10:6. [DOI: 10.12688/f1000research.26997.2] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
24 Weissler EH, Naumann T, Andersson T, Ranganath R, Elemento O, Luo Y, Freitag DF, Benoit J, Hughes MC, Khan F, Slater P, Shameer K, Roe M, Hutchison E, Kollins SH, Broedl U, Meng Z, Wong JL, Curtis L, Huang E, Ghassemi M. The role of machine learning in clinical research: transforming the future of evidence generation. Trials 2021;22:537. [PMID: 34399832 DOI: 10.1186/s13063-021-05489-x] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
25 Fiske A, Henningsen P, Buyx A. Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy. J Med Internet Res 2019;21:e13216. [PMID: 31094356 DOI: 10.2196/13216] [Cited by in Crossref: 64] [Cited by in F6Publishing: 31] [Article Influence: 21.3] [Reference Citation Analysis]
26 Babel A, Taneja R, Mondello Malvestiti F, Monaco A, Donde S. Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases. Front Digit Health 2021;3:669869. [PMID: 34713142 DOI: 10.3389/fdgth.2021.669869] [Reference Citation Analysis]
27 Ray A, Bhardwaj A, Malik YK, Singh S, Gupta R. Artificial intelligence and Psychiatry: An overview. Asian Journal of Psychiatry 2022. [DOI: 10.1016/j.ajp.2022.103021] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
28 Woo M. An AI boost for clinical trials. Nature 2019;573:S100-2. [DOI: 10.1038/d41586-019-02871-3] [Cited by in Crossref: 24] [Cited by in F6Publishing: 16] [Article Influence: 8.0] [Reference Citation Analysis]
29 Wu H, Yin H, Chen H, Sun M, Liu X, Yu Y, Tang Y, Long H, Zhang B, Zhang J, Zhou Y, Li Y, Zhang G, Zhang P, Zhan Y, Liao J, Luo S, Xiao R, Su Y, Zhao J, Wang F, Zhang J, Zhang W, Zhang J, Lu Q. A deep learning, image based approach for automated diagnosis for inflammatory skin diseases. Ann Transl Med 2020;8:581. [PMID: 32566608 DOI: 10.21037/atm.2020.04.39] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 3.5] [Reference Citation Analysis]
30 Krittanawong C, Johnson KW, Tang WW. How artificial intelligence could redefine clinical trials in cardiovascular medicine: lessons learned from oncology.Per Med. 2019;16:83-88. [PMID: 30838909 DOI: 10.2217/pme-2018-0130] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
31 Van Biesen W, Decruyenaere J, Sideri K, Cockbain J, Sterckx S. Remote digital monitoring of medication intake: methodological, medical, ethical and legal reflections. Acta Clin Belg 2021;76:209-16. [PMID: 31870225 DOI: 10.1080/17843286.2019.1708152] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
32 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 Uhealth 2022;10:e35157. [PMID: 35266873 DOI: 10.2196/35157] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
33 Salcedo J, Rosales M, Kim JS, Nuno D, Suen SC, Chang AH. Cost-effectiveness of artificial intelligence monitoring for active tuberculosis treatment: A modeling study. PLoS One 2021;16:e0254950. [PMID: 34288951 DOI: 10.1371/journal.pone.0254950] [Reference Citation Analysis]
34 Chivilgina O, Elger BS, Jotterand F. Digital Technologies for Schizophrenia Management: A Descriptive Review. Sci Eng Ethics 2021;27:25. [PMID: 33835287 DOI: 10.1007/s11948-021-00302-z] [Reference Citation Analysis]
35 Gandhi M, Bacchetti P, Spinelli MA, Okochi H, Baeten JM, Siriprakaisil O, Klinbuayaem V, Rodrigues WC, Wang G, Vincent M, Cressey TR, Drain PK. 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. J Acquir Immune Defic Syndr 2019;81:72-7. [PMID: 30664078 DOI: 10.1097/QAI.0000000000001971] [Cited by in Crossref: 28] [Cited by in F6Publishing: 21] [Article Influence: 9.3] [Reference Citation Analysis]
36 Velligan DI, Maples NJ, Pokorny JJ, Wright C. Assessment of adherence to oral antipsychotic medications: What has changed over the past decade? Schizophrenia Research 2020;215:17-24. [DOI: 10.1016/j.schres.2019.11.022] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 3.5] [Reference Citation Analysis]
37 Koesmahargyo V, Abbas A, Zhang L, Guan L, Feng S, Yadav V, Galatzer-Levy IR. Accuracy of machine learning-based prediction of medication adherence in clinical research. Psychiatry Res 2020;294:113558. [PMID: 33242836 DOI: 10.1016/j.psychres.2020.113558] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
38 Dockendorf MF, Hansen BJ, Bateman KP, Moyer M, Shah JK, Shipley LA. Digitally Enabled, Patient-Centric Clinical Trials: Shifting the Drug Development Paradigm. Clin Transl Sci 2021;14:445-59. [PMID: 33048475 DOI: 10.1111/cts.12910] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 1.5] [Reference Citation Analysis]