AI and Opportunities in Cancer Care

Authors

  • Sunder Singh Department of Radiation Oncology, Pt. BD Sharma PGIMS, Rohtak, Haryana, India.
  • Abhshek Soni Department of Radiation Oncology, Pt. BD Sharma PGIMS, Rohtak, Haryana, India.
  • Rakesh Dhankhar Department of Radiation Oncology, Pt. BD Sharma PGIMS, Rohtak, Haryana, India.
  • Vivek Kaushal Department of Radiation Oncology, Pt. BD Sharma PGIMS, Rohtak, Haryana, India.
  • Ashok Chauhan Department of Radiation Oncology, Pt. BD Sharma PGIMS, Rohtak, Haryana, India.
  • Rajeev Atri Department of Radiation Oncology, Pt. BD Sharma PGIMS, Rohtak, Haryana, India.

DOI:

https://doi.org/10.9734/bpi/cpms/v2/16367D

Keywords:

Artificial intelligence, technology, cancer, optimum utilization

Abstract

Artificial intelligence (AI) is the use of algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. While the human mind is limited to process huge data in a narrow time range, AI has the potential of processing huge previous data and thus provide optimal decision-making. AI-based algorithms hold great promise to pave the way to identify the genetic mutations and aberrant protein interactions at a very early stage. AI thus provides great opportunities and in the form of assistance to pathologists and physicians which 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. The main objective of the research is to efficiently use the technology in the form of artificial intelligence and cure the cancer patients.

Published

2022-06-21

How to Cite

Sunder Singh, Abhshek Soni, Rakesh Dhankhar, Vivek Kaushal, Ashok Chauhan, & Rajeev Atri. (2022). AI and Opportunities in Cancer Care. Current Practice in Medical Science Vol. 2, 1–10. https://doi.org/10.9734/bpi/cpms/v2/16367D