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Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future.
Iqbal, Muhammad Javed; Javed, Zeeshan; Sadia, Haleema; Qureshi, Ijaz A; Irshad, Asma; Ahmed, Rais; Malik, Kausar; Raza, Shahid; Abbas, Asif; Pezzani, Raffaele; Sharifi-Rad, Javad.
Afiliação
  • Iqbal MJ; Department of Biotechnology, Faculty of Sciences, University of Sialkot, Sialkot, Pakistan.
  • Javed Z; Office for Research Innovation and Commercialization (ORIC), Lahore Garrison University, Sector-C, DHA Phase-VI, Lahore, Pakistan. zeeshan_javed456@yahoo.com.
  • Sadia H; Department of Biotechnology, Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS), Quetta, Pakistan.
  • Qureshi IA; Talon Institute of Higher Studies, Lahore, Pakistan.
  • Irshad A; Department of Life Sciences, University of Management Sciences and Technology, Lahore, Pakistan.
  • Ahmed R; Department of Microbiology, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan.
  • Malik K; Center for Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan.
  • Raza S; Office for Research Innovation and Commercialization (ORIC), Lahore Garrison University, Sector-C, DHA Phase-VI, Lahore, Pakistan.
  • Abbas A; Department of Biotechnology, Faculty of Sciences, University of Sialkot, Sialkot, Pakistan.
  • Pezzani R; Dept. Medicine (DIMED), OU Endocrinology, University of Padova, via Ospedale 105, 35128, Padova, Italy. raffaele.pezzani@gmail.com.
  • Sharifi-Rad J; AIROB, Associazione Italiana Per La Ricerca Oncologica Di Base, Padova, Italy. raffaele.pezzani@gmail.com.
Cancer Cell Int ; 21(1): 270, 2021 May 21.
Article em En | MEDLINE | ID: mdl-34020642
ABSTRACT
Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: Cancer Cell Int Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Paquistão

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: Cancer Cell Int Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Paquistão