From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2023-12-01
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| Series: | Open Life Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/biol-2022-0777 |
| _version_ | 1797387336987705344 |
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| author | Verma Jyoti Sandhu Archana Popli Renu Kumar Rajeev Khullar Vikas Kansal Isha Sharma Ashutosh Garg Kanwal Kashyap Neeru Aurangzeb Khursheed |
| author_facet | Verma Jyoti Sandhu Archana Popli Renu Kumar Rajeev Khullar Vikas Kansal Isha Sharma Ashutosh Garg Kanwal Kashyap Neeru Aurangzeb Khursheed |
| author_sort | Verma Jyoti |
| collection | DOAJ |
| first_indexed | 2024-03-08T22:22:43Z |
| format | Article |
| id | doaj.art-8a89dec14bb444458018bed15d38613f |
| institution | Directory Open Access Journal |
| issn | 2391-5412 |
| language | English |
| last_indexed | 2024-03-08T22:22:43Z |
| publishDate | 2023-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Life Sciences |
| spelling | doaj.art-8a89dec14bb444458018bed15d38613f2023-12-18T12:42:46ZengDe GruyterOpen Life Sciences2391-54122023-12-011819081410.1515/biol-2022-0777From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histologyVerma Jyoti0Sandhu Archana1Popli Renu2Kumar Rajeev3Khullar Vikas4Kansal Isha5Sharma Ashutosh6Garg Kanwal7Kashyap Neeru8Aurangzeb Khursheed9Department of Computer Science and Engineering, Punjabi University, Patiala, IndiaMM Institute of Computer Technology and Business Management Maharishi Markandeshwar (Deemed to be University) Mullana-Ambala, Haryana, 134007, IndiaChitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IndiaChitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IndiaChitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IndiaChitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IndiaDepartment of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun248007, Uttarakhand, IndiaDepartment of Computer Science and Applications, Kurukshetra University, Kurukshetra, 136119, Haryana, IndiaDepartment of ECE, M.M. Engineering College, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Ambala, Haryana 134007, IndiaDepartment of Computer Engineering, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh11543, Saudi Arabiahttps://doi.org/10.1515/biol-2022-0777prognostic survival predictioncolorectal cancerdeep learninghistopathological analysisretrospective multicenter studyimage patches |
| spellingShingle | Verma Jyoti Sandhu Archana Popli Renu Kumar Rajeev Khullar Vikas Kansal Isha Sharma Ashutosh Garg Kanwal Kashyap Neeru Aurangzeb Khursheed From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology Open Life Sciences prognostic survival prediction colorectal cancer deep learning histopathological analysis retrospective multicenter study image patches |
| title | From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology |
| title_full | From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology |
| title_fullStr | From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology |
| title_full_unstemmed | From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology |
| title_short | From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology |
| title_sort | from slides to insights harnessing deep learning for prognostic survival prediction in human colorectal cancer histology |
| topic | prognostic survival prediction colorectal cancer deep learning histopathological analysis retrospective multicenter study image patches |
| url | https://doi.org/10.1515/biol-2022-0777 |
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