This paper is in the following e-collection/theme issue:

Artificial Intelligence (1371) Machine Learning (1465) Decision Support for Health Professionals (1185) Innovations and Technology in Cancer Care (423)

Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23483, first published .
Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review

Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review

Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review

Authors of this article:

Owain T Jones1 Author Orcid Image ;   Natalia Calanzani1 Author Orcid Image ;   Smiji Saji1 Author Orcid Image ;   Stephen W Duffy2 Author Orcid Image ;   Jon Emery3 Author Orcid Image ;   Willie Hamilton4 Author Orcid Image ;   Hardeep Singh5 Author Orcid Image ;   Niek J de Wit6 Author Orcid Image ;   Fiona M Walter1 Author Orcid Image
Article Authors Cited by (30) Tweetations (32) Metrics

Journals

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  2. Jones O, Matin R, van der Schaar M, Prathivadi Bhayankaram K, Ranmuthu C, Islam M, Behiyat D, Boscott R, Calanzani N, Emery J, Williams H, Walter F. Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review. The Lancet Digital Health 2022;4(6):e466 View
  3. Lee C, Light A, Saveliev E, van der Schaar M, Gnanapragasam V. Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer. npj Digital Medicine 2022;5(1) View
  4. Martinez-Millana A, Saez-Saez A, Tornero-Costa R, Azzopardi-Muscat N, Traver V, Novillo-Ortiz D. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews. International Journal of Medical Informatics 2022;166:104855 View
  5. Feduniw S, Golik D, Kajdy A, Pruc M, Modzelewski J, Sys D, Kwiatkowski S, Makomaska-Szaroszyk E, Rabijewski M. Application of Artificial Intelligence in Screening for Adverse Perinatal Outcomes—A Systematic Review. Healthcare 2022;10(11):2164 View
  6. Samimi G, Douglas J, Heckman-Stoddard B, Ford L, Szabo E, Minasian L. Report from an NCI Roundtable: Cancer Prevention in Primary Care. Cancer Prevention Research 2022;15(5):273 View
  7. Black G, Bhuiya A, Friedemann Smith C, Hirst Y, Nicholson B. Harnessing the Electronic Health Care Record to Optimize Patient Safety in Primary Care: Framework for Evaluating e–Safety-Netting Tools. JMIR Medical Informatics 2022;10(8):e35726 View
  8. Taber P, Armin J, Orozco G, Del Fiol G, Erdrich J, Kawamoto K, Israni S. Artificial Intelligence and Cancer Control: Toward Prioritizing Justice, Equity, Diversity, and Inclusion (JEDI) in Emerging Decision Support Technologies. Current Oncology Reports 2023;25(5):387 View
  9. Briggs E, de Kamps M, Hamilton W, Johnson O, McInerney C, Neal R. Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools. Cancers 2022;14(20):5023 View
  10. Li Y, Zhu P, Zhang G, Yu Y. Improving Seaport Wharf Maintenance and Safety with Structural Health Monitoring System in High Salt and Humidity Environments. Sustainability 2023;15(5):4472 View
  11. de Souza L, Fonseca F, Araújo A, Lopes M, Vargas P, Khurram S, Kowalski L, dos Santos H, Warnakulasuriya S, Dolezal J, Pearson A, Santos‐Silva A. Machine learning for detection and classification of oral potentially malignant disorders: A conceptual review. Journal of Oral Pathology & Medicine 2023;52(3):197 View
  12. Cabral B, Braga L, Syed-Abdul S, Mota F. Future of Artificial Intelligence Applications in Cancer Care: A Global Cross-Sectional Survey of Researchers. Current Oncology 2023;30(3):3432 View
  13. Alanazi A, Almutib A, Aldosari B. Physicians’ Perspectives on a Multi-Dimensional Model for the Roles of Electronic Health Records in Approaching a Proper Differential Diagnosis. Journal of Personalized Medicine 2023;13(4):680 View
  14. Jiao W, Zhang X, D’Souza F. The Economic Value and Clinical Impact of Artificial Intelligence in Healthcare: A Scoping Literature Review. IEEE Access 2023;11:123445 View
  15. Kolasa K, Admassu B, Hołownia-Voloskova M, Kędzior K, Poirrier J, Perni S. Systematic reviews of machine learning in healthcare: a literature review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(1):63 View
  16. Rahman M, Akbar M, Leiva V, Martin-Barreiro C, Imran M, Riaz M, Castro C. An IoT-fuzzy intelligent approach for holistic management of COVID-19 patients. Heliyon 2024;10(1):e22454 View
  17. Wenderott K, Krups J, Luetkens J, Gambashidze N, Weigl M. Prospective effects of an artificial intelligence-based computer-aided detection system for prostate imaging on routine workflow and radiologists’ outcomes. European Journal of Radiology 2024;170:111252 View
  18. Braga L, Lopes R, Alves L, Mota F. The global patent landscape of artificial intelligence applications for cancer. Nature Biotechnology 2023;41(12):1679 View
  19. Koskela T, Esteva M, Mangione M, Contreras Martos S, Hajdarevic S, Högberg C, Marzo-Castillejo M, Sawicka-Powierza J, Siliņa V, Harris M, Petek D. What would primary care practitioners do differently after a delayed cancer diagnosis? Learning lessons from their experiences. Scandinavian Journal of Primary Health Care 2024;42(1):123 View
  20. Evans R, Bryant L, Russell G, Absolom K. Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review. International Journal of Medical Informatics 2024;183:105342 View
  21. Myslicka M, Kawala-Sterniuk A, Bryniarska A, Sudol A, Podpora M, Gasz R, Martinek R, Kahankova Vilimkova R, Vilimek D, Pelc M, Mikolajewski D. Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes. Archives of Dermatological Research 2024;316(4) View
  22. Gondode P, Duggal S, Mahor V. Artificial intelligence hallucinations in anaesthesia: Causes, consequences and countermeasures. Indian Journal of Anaesthesia 2024;68(7):658 View
  23. Swinckels L, Bennis F, Ziesemer K, Scheerman J, Bijwaard H, de Keijzer A, Bruers J. The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review. Journal of Medical Internet Research 2024;26:e48320 View
  24. Portz J, Moore S, Bull S. Evolutionary Trends in the Adoption, Adaptation, and Abandonment of Mobile Health Technologies: Viewpoint Based on 25 Years of Research. Journal of Medical Internet Research 2024;26:e62790 View

Books/Policy Documents

  1. Chandraprabha R, Singh S. Emerging Research in Computing, Information, Communication and Applications. View
  2. Lidströmer N, Davids J, Sood H, Ashrafian H. Artificial Intelligence in Medicine. View
  3. Lidströmer N, Davids J, Sood H, Ashrafian H. Artificial Intelligence in Medicine. View
  4. Sharma I, Sharma A, Tomer R, Negi N, Sobti R. Handbook of Oncobiology: From Basic to Clinical Sciences. View
  5. Sharma I, Sharma A, Tomer R, Negi N, Sobti R. Handbook of Oncobiology: From Basic to Clinical Sciences. View
  6. Takawira B, Chadyiwa M, Pooe D. Resiliency Strategies for Long-Term Business Success. View