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

  • Muhammad Javed Iqbal
  • , Zeeshan Javed
  • , Haleema Sadia
  • , Ijaz A. Qureshi
  • , Asma Irshad
  • , Rais Ahmed
  • , Kausar Malik
  • , Shahid Raza
  • , Asif Abbas
  • , Raffaele Pezzani
  • , Javad Sharifi-Rad
  • University of Sialkot
  • Lahore Garrison University
  • Balochistan University of Information Technology, Engineering and Management Sciences
  • Talon Institute of Higher Studies
  • Lahore University of Management Sciences
  • Cholistan University of Veterinary and Animal Sciences (CUVAS)
  • University of the Punjab
  • University of Padua
  • Associazione Italiana per la Ricerca Oncologica di Base
  • Shahid Beheshti University of Medical Sciences
  • Universidad del Azuay

Research output: Contribution to journalReview articlepeer-review

301 Scopus citations

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.

Original languageEnglish
Article number270
JournalCancer Cell International
Volume21
Issue number1
DOIs
StatePublished - Dec 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Artificial intelligence
  • Cancer diagnosis
  • Machine learning
  • Therapeutic interventions
  • Treatment

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