BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

292 related articles for article (PubMed ID: 37982736)

  • 1. Exploring the feasibility of an artificial intelligence based clinical decision support system for cutaneous melanoma detection in primary care - a mixed method study.
    Helenason J; Ekström C; Falk M; Papachristou P
    Scand J Prim Health Care; 2024 Mar; 42(1):51-60. PubMed ID: 37982736
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Clinical Decision Support System for Sleep Staging Tasks With Explanations From Artificial Intelligence: User-Centered Design and Evaluation Study.
    Hwang J; Lee T; Lee H; Byun S
    J Med Internet Res; 2022 Jan; 24(1):e28659. PubMed ID: 35044311
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.
    Maron RC; Utikal JS; Hekler A; Hauschild A; Sattler E; Sondermann W; Haferkamp S; Schilling B; Heppt MV; Jansen P; Reinholz M; Franklin C; Schmitt L; Hartmann D; Krieghoff-Henning E; Schmitt M; Weichenthal M; von Kalle C; Fröhling S; Brinker TJ
    J Med Internet Res; 2020 Sep; 22(9):e18091. PubMed ID: 32915161
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study.
    Nelson CA; Pérez-Chada LM; Creadore A; Li SJ; Lo K; Manjaly P; Pournamdari AB; Tkachenko E; Barbieri JS; Ko JM; Menon AV; Hartman RI; Mostaghimi A
    JAMA Dermatol; 2020 May; 156(5):501-512. PubMed ID: 32159733
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence-Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation.
    Fujimori R; Liu K; Soeno S; Naraba H; Ogura K; Hara K; Sonoo T; Ogura T; Nakamura K; Goto T
    JMIR Form Res; 2022 Jun; 6(6):e36501. PubMed ID: 35699995
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Physicians' Perspectives on AI in Clinical Decision Support Systems: Interview Study of the CURATE.AI Personalized Dose Optimization Platform.
    Vijayakumar S; Lee VV; Leong QY; Hong SJ; Blasiak A; Ho D
    JMIR Hum Factors; 2023 Oct; 10():e48476. PubMed ID: 37902825
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Are physicians ready for precision antibiotic prescribing? A qualitative analysis of the acceptance of artificial intelligence-enabled clinical decision support systems in India and Singapore.
    Huang Z; George MM; Tan YR; Natarajan K; Devasagayam E; Tay E; Manesh A; Varghese GM; Abraham OC; Zachariah A; Yap P; Lall D; Chow A
    J Glob Antimicrob Resist; 2023 Dec; 35():76-85. PubMed ID: 37640155
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults.
    Ferrante di Ruffano L; Takwoingi Y; Dinnes J; Chuchu N; Bayliss SE; Davenport C; Matin RN; Godfrey K; O'Sullivan C; Gulati A; Chan SA; Durack A; O'Connell S; Gardiner MD; Bamber J; Deeks JJ; Williams HC;
    Cochrane Database Syst Rev; 2018 Dec; 12(12):CD013186. PubMed ID: 30521691
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluation of an artificial intelligence-based decision support for detection of cutaneous melanoma in primary care - a prospective, real-life, clinical trial.
    Papachristou P; Söderholm M; Pallon J; Taloyan M; Polesie S; Paoli J; Anderson CD; Falk M
    Br J Dermatol; 2024 Jan; ():. PubMed ID: 38234043
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Diagnostic capacity of skin tumor artificial intelligence-assisted decision-making software in real-world clinical settings.
    Li CX; Fei WM; Shen CB; Wang ZY; Jing Y; Meng RS; Cui Y
    Chin Med J (Engl); 2020 Sep; 133(17):2020-2026. PubMed ID: 32810047
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Implementation of artificial intelligence for the detection of cutaneous melanoma within a primary care setting: prevalence and types of skin cancer in outdoor enthusiasts.
    Miller IJ; Stapelberg M; Rosic N; Hudson J; Coxon P; Furness J; Walsh J; Climstein M
    PeerJ; 2023; 11():e15737. PubMed ID: 37576493
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Development and Evaluation of a Mobile Decision Support System for Hypertension Management in the Primary Care Setting in Brazil: Mixed-Methods Field Study on Usability, Feasibility, and Utility.
    Silveira DV; Marcolino MS; Machado EL; Ferreira CG; Alkmim MBM; Resende ES; Carvalho BC; Antunes AP; Ribeiro ALP
    JMIR Mhealth Uhealth; 2019 Mar; 7(3):e9869. PubMed ID: 30907740
    [TBL] [Abstract][Full Text] [Related]  

  • 13. "Many roads lead to Rome and the Artificial Intelligence only shows me one road": an interview study on physician attitudes regarding the implementation of computerised clinical decision support systems.
    Van Cauwenberge D; Van Biesen W; Decruyenaere J; Leune T; Sterckx S
    BMC Med Ethics; 2022 May; 23(1):50. PubMed ID: 35524301
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Development and Assessment of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices.
    Jain A; Way D; Gupta V; Gao Y; de Oliveira Marinho G; Hartford J; Sayres R; Kanada K; Eng C; Nagpal K; DeSalvo KB; Corrado GS; Peng L; Webster DR; Dunn RC; Coz D; Huang SJ; Liu Y; Bui P; Liu Y
    JAMA Netw Open; 2021 Apr; 4(4):e217249. PubMed ID: 33909055
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting.
    Giavina-Bianchi M; de Sousa RM; Paciello VZA; Vitor WG; Okita AL; Prôa R; Severino GLDS; Schinaid AA; Espírito Santo R; Machado BS
    PLoS One; 2021; 16(9):e0257006. PubMed ID: 34550970
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Feasibility study of a clinical decision support system for the management of multimorbid seniors in primary care: study protocol.
    Weltermann B; Kersting C
    Pilot Feasibility Stud; 2016; 2():16. PubMed ID: 27965836
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Evaluating the Clinical Feasibility of an Artificial Intelligence-Powered, Web-Based Clinical Decision Support System for the Treatment of Depression in Adults: Longitudinal Feasibility Study.
    Popescu C; Golden G; Benrimoh D; Tanguay-Sela M; Slowey D; Lundrigan E; Williams J; Desormeau B; Kardani D; Perez T; Rollins C; Israel S; Perlman K; Armstrong C; Baxter J; Whitmore K; Fradette MJ; Felcarek-Hope K; Soufi G; Fratila R; Mehltretter J; Looper K; Steiner W; Rej S; Karp JF; Heller K; Parikh SV; McGuire-Snieckus R; Ferrari M; Margolese H; Turecki G
    JMIR Form Res; 2021 Oct; 5(10):e31862. PubMed ID: 34694234
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Usability Evaluation of a Clinical Decision Support System for Geriatric ED Pain Treatment.
    Genes N; Kim MS; Thum FL; Rivera L; Beato R; Song C; Soriano J; Kannry J; Baumlin K; Hwang U
    Appl Clin Inform; 2016; 7(1):128-42. PubMed ID: 27081412
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An AI-Powered Clinical Decision Support System to Predict Flares in Rheumatoid Arthritis: A Pilot Study.
    Labinsky H; Ukalovic D; Hartmann F; Runft V; Wichmann A; Jakubcik J; Gambel K; Otani K; Morf H; Taubmann J; Fagni F; Kleyer A; Simon D; Schett G; Reichert M; Knitza J
    Diagnostics (Basel); 2023 Jan; 13(1):. PubMed ID: 36611439
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Decision-support tools via mobile devices to improve quality of care in primary healthcare settings.
    Agarwal S; Glenton C; Tamrat T; Henschke N; Maayan N; Fønhus MS; Mehl GL; Lewin S
    Cochrane Database Syst Rev; 2021 Jul; 7(7):CD012944. PubMed ID: 34314020
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.