Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future

Cancer Cell International

Kausar Malik¹  Haleema Sadia²  Asif Abbas³  Muhammad Javed Iqbal³  Asma Irshad⁴  Rais Ahmed⁵  Raffaele Pezzani⁶  Shahid Raza⁷  Zeeshan Javed⁷  Javad Sharifi-Rad⁸  Ijaz A. Qureshi⁹ 

[1] Center for Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan;Department of Biotechnology, Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS), Quetta, Pakistan;Department of Biotechnology, Faculty of Sciences, University of Sialkot, Sialkot, Pakistan;Department of Life Sciences, University of Management Sciences and Technology, Lahore, Pakistan;Department of Microbiology, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan;Dept. Medicine (DIMED), OU Endocrinology, University of Padova, via Ospedale 105, 35128, Padova, Italy;AIROB, Associazione Italiana Per La Ricerca Oncologica Di Base, Padova, Italy;Office for Research Innovation and Commercialization (ORIC), Lahore Garrison University, Sector-C, DHA Phase-VI, Lahore, Pakistan;Phytochemistry Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran;Facultad de Medicina, Universidad del Azuay, Cuenca, Ecuador;Talon Institute of Higher Studies, Lahore, Pakistan;

关键词: Artificial intelligence;    Machine learning;    Cancer diagnosis;    Treatment;    Therapeutic interventions;   

DOI  :  10.1186/s12935-021-01981-1

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY