Artificial intelligence in radiation Oncology, and Molecular pathways in cancer
Document Type
News Article
Abstract
Artificial intelligence has tremendous unexplored potential in medicine, especially in radiation oncology, since it generates a large volume of data. Collaborating with data-scientists from MIT, Manipal and Philips, Bangalore, we have looked at possibilities of artificial intelligence in predicting disease outcomes of radiotherapy in head and neck cancers using clinic-pathological data as input. Additionally, a project on toxicity prediction of radiotherapy using the Dose-Volume-Histogram data from the patient radiotherapy plans is also being carried out.
Determination of the role of biological pathways in the behavior and outcomes of cervical cancer is another domain of research actively being pursued in association with the scientists from School of Life Sciences, Manipal. One project is studying the role of clustered miRNA in cervical cancer development and progression, and its prognostic relevance. The other two are focused towards oncogenic HPV and cervical cancers, and determining the association between the microbiome and cervical cancer.
Publications:
Gangil, T., Shahabuddin, A. B., Dinesh Rao, B., Palanisamy, K., Chakrabarti, B., & Sharan, K. Predicting clinical outcomes of radiotherapy for head and neck squamous cell carcinoma patients using machine learning algorithms. Journal of Big Data, 2022;9(1):1-19.
Bhat S, Kabekkodu SP, Adiga D, Fernandes R, Shukla V, Bhandari P, Pandey D, Sharan K, Satyamoorthy K. ZNF471 modulates EMT and functions as methylation regulated tumor suppressor with diagnostic and prognostic significance in cervical cancer. Cell Biology and Toxicology 2021;37:731-49.
Adiga D, Eswaran S, Pandey D, Sharan K, Kabekkodu SP. Molecular landscape of recurrent cervical cancer. Critical Reviews in Oncology/Hematology 2021;157:103178.
Nair SS, Devi VM, Sharan K, Nagesh J. Analysis of Planning Target Volume Margin on Different Immobilization Devices for Radiotherapy in Carcinoma Breast. JK Science: Journal of Medical Education & Research. 2022;24(2):113-7.
Weblink: https://www.scopus.com/authid/detail.uri?authorId=57217333136
Publication Date
Spring 10-1-2022
Recommended Citation
Sharan, Krishna Dr, "Artificial intelligence in radiation Oncology, and Molecular pathways in cancer" (2022). Health collection. 66.
https://impressions.manipal.edu/health-collection/66
