Open Life Sciences (Dec 2023)
From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology
- Verma Jyoti,
- Sandhu Archana,
- Popli Renu,
- Kumar Rajeev,
- Khullar Vikas,
- Kansal Isha,
- Sharma Ashutosh,
- Garg Kanwal,
- Kashyap Neeru,
- Aurangzeb Khursheed
Affiliations
- Verma Jyoti
- Department of Computer Science and Engineering, Punjabi University, Patiala, India
- Sandhu Archana
- MM Institute of Computer Technology and Business Management Maharishi Markandeshwar (Deemed to be University) Mullana-Ambala, Haryana, 134007, India
- Popli Renu
- Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
- Kumar Rajeev
- Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
- Khullar Vikas
- Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
- Kansal Isha
- Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
- Sharma Ashutosh
- Department of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun248007, Uttarakhand, India
- Garg Kanwal
- Department of Computer Science and Applications, Kurukshetra University, Kurukshetra, 136119, Haryana, India
- Kashyap Neeru
- Department of ECE, M.M. Engineering College, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Ambala, Haryana 134007, India
- Aurangzeb Khursheed
- Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh11543, Saudi Arabia
- DOI
- https://doi.org/10.1515/biol-2022-0777
- Journal volume & issue
-
Vol. 18,
no. 1
pp. 908 – 14
Abstract
No abstracts available.Keywords
- prognostic survival prediction
- colorectal cancer
- deep learning
- histopathological analysis
- retrospective multicenter study
- image patches