utd_medknow
Indian Journal of Cancer
Home  ICS  Feedback Subscribe Top cited articles Login 
Users Online :1041
Small font sizeDefault font sizeIncrease font size
Resource Links
     Search Pubmed for
 
    -  Majumder A
    -  Sen D
 

 Article Access Statistics
    Viewed101    
    PDF Downloaded7    

Recommend this journal

 

 REVIEW ARTICLE

Artificial intelligence in cancer diagnostics and therapy: current perspectives


1 Department of Pathology, Armed Forces Medical College and Command Hospital (Southern Command), Pune, Maharashtra, India
2 Department of Radiodiagnosis, Armed Forces Medical College and Command Hospital (Southern Command), Pune, Maharashtra, India

Correspondence Address:
Debraj Sen,
Department of Radiodiagnosis, Armed Forces Medical College and Command Hospital (Southern Command), Pune, Maharashtra
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijc.IJC_399_20

Artificial intelligence (AI) has found its way into every sphere of human life including the field of medicine. Detection of cancer might be AI's most altruistic and convoluted challenge to date in the field of medicine. Embedding AI into various aspects of cancer diagnostics would be of immense use in dealing with the tedious, repetitive, time-consuming job of lesion detection, remove opportunities for human error, and cut costs and time. This would be of great value in cancer screening programs. By using AI algorithms, data from digital images from radiology and pathology that are imperceptible to the human eye can be identified (radiomics and pathomics). Correlating radiomics and pathomics with clinico-demographic-therapy-morbidity-mortality profiles will lead to a greater understanding of cancers. Specific imaging phenotypes have been found to be associated with specific gene-determined molecular pathways involved in cancer pathogenesis (radiogenomics). All these developments would not only help to personalize oncologic practice but also lead to the development of new imaging biomarkers. AI algorithms in oncoimaging and oncopathology will broadly have the following uses: cancer screening (detection of lesions), characterization and grading of tumors, and clinical decision-making and prognostication. However, AI cannot be a foolproof panacea nor can it supplant the role of humans. It can however be a powerful and useful complement to human insights and deeper understanding. Multiple issues like standardization, validity, ethics, privacy, finances, legal liability, training, accreditation, etc., need to be overcome before the vast potential of AI in diagnostic oncology can be fully harnessed.




  Site Map | What's new | Copyright and Disclaimer
  Online since 1st April '07
  2007 - Indian Journal of Cancer | Published by Wolters Kluwer - Medknow