Machine Learning for Predicting Colorectal Cancer and Advanced Colorectal Polyps
The review underscores the significant role of ML in CRC and ACP diagnosis and its routine use could efficiently direct high-risk patients to timely colonoscopies and spare the low-risk ones from unnecessary procedures. Despite the promise shown, the variability in methodologies and outcomes highlights the need for standardized approaches and further investigation in this field.
Authors
- Douglas G. Adler (ORCID: https://orcid.org/0000-0003-3214-6285)
- Sheza Malik (ORCID: https://orcid.org/0000-0003-3026-2426)
- Raseen Tariq (ORCID: https://orcid.org/0000-0001-7586-6691)
- Faiqa Farrukh
- Bettina Gabrielle Tenorio (ORCID: https://orcid.org/0000-0002-9173-8427)
- Ahmad Abu Turab Naqvi
Institutions
- Mayo Clinic (US)
- Ateneo de Manila University (PH)
- Porter Adventist Hospital (US)
- Rochester General Hospital (US)
- Jefferson Hospital (US)
Publication Details
- Journal
- Journal of Clinical Gastroenterology
- Published
- 2025-05-28
- DOI
- https://doi.org/10.1097/mcg.0000000000002172
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08