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

Digital Health Reviews (1174) Artificial Intelligence (1186) Machine Learning (1370) Innovations and Technology in Cancer Care (400)

Published on in Vol 24, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36490, first published .
A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects

A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects

A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects

Authors of this article:

Yousra El Alaoui1 Author Orcid Image ;   Adel Elomri1 Author Orcid Image ;   Marwa Qaraqe1 Author Orcid Image ;   Regina Padmanabhan1 Author Orcid Image ;   Ruba Yasin Taha2 Author Orcid Image ;   Halima El Omri2 Author Orcid Image ;   Abdelfatteh EL Omri3 Author Orcid Image ;   Omar Aboumarzouk3, 4, 5 Author Orcid Image
Article Authors Cited by (12) Tweetations (7) Metrics

Journals

  1. Padmanabhan R, Elomri A, Taha R, El Omri H, Elsabah H, El Omri A. Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care. International Journal of Environmental Research and Public Health 2022;20(1):526 View
  2. Dowling M, Efstathiou N, Drury A, Semple C, Fernández-Ortega P, Brochstedt Dieperink K, Pape E, Kotronoulas G, Miguel S, Colomer-Lahiguera S, Bağçivan G. Cancer nursing research priorities: A rapid review. European Journal of Oncology Nursing 2023;63:102272 View
  3. Walter W, Pohlkamp C, Meggendorfer M, Nadarajah N, Kern W, Haferlach C, Haferlach T. Artificial intelligence in hematological diagnostics: Game changer or gadget?. Blood Reviews 2023;58:101019 View
  4. Su J, Liu Y, Zhang J, Han J, Song J. CDC-NET: a cell detection and confirmation network of bone marrow aspirate images for the aided diagnosis of AML. Medical & Biological Engineering & Computing 2024;62(2):575 View
  5. Fan B, Yong B, Li R, Wang S, Aw M, Chia M, Chen D, Neo Y, Occhipinti B, Ling R, Ramanathan K, Ong Y, Lim K, Wong W, Lim S, Latiff S, Shanmugam H, Wong M, Ponnudurai K, Winkler S. From microscope to micropixels: A rapid review of artificial intelligence for the peripheral blood film. Blood Reviews 2024;64:101144 View
  6. Tavakkoli Shiraji S, Sanaei M. The application of artificial intelligence (AI) in the diagnosis of platelet disorders. Iranian Journal of Blood and Cancer 2023;15(3):68 View
  7. Alanzi T, Alanazi F, Mashhour B, Altalhi R, Alghamdi A, Al Shubbar M, Alamro S, Alshammari M, Almusmili L, Alanazi L, Alzahrani S, Alalouni R, Alanzi N, Alsharifa A. Surveying Hematologists’ Perceptions and Readiness to Embrace Artificial Intelligence in Diagnosis and Treatment Decision-Making. Cureus 2023 View
  8. Elshoeibi A, Badr A, Elsayed B, Metwally O, Elshoeibi R, Elhadary M, Elshoeibi A, Attya M, Khadadah F, Alshurafa A, Alhuraiji A, Yassin M. Integrating AI and ML in Myelodysplastic Syndrome Diagnosis: State-of-the-Art and Future Prospects. Cancers 2023;16(1):65 View
  9. Hadiloo K, Taremi S, Safa S, Amidifar S, Esmaeilzadeh A. The new era of immunological treatment, last updated and future consideration of CAR T cell-based drugs. Pharmacological Research 2024;203:107158 View
  10. Hou H, Zhang R, Li J. Artificial intelligence in the clinical laboratory. Clinica Chimica Acta 2024;559:119724 View

Books/Policy Documents

  1. Luvhengo T, Molefi T, Demetriou D, Hull R, Dlamini Z. Artificial Intelligence and Precision Oncology. View