Prediction of early-onset colorectal cancer mortality rates in the United States using machine learning.

Journal: Cancer medicine

PMID: 38149332

Abstract

INTRODUCTION: The current study, focusing on a significant US (United States) colorectal cancer (CRC) burden, employs machine learning for predicting future rates among young population.

Authors

Hassam Ali

Department of Gastroenterology, East Carolina University/Brody School of Medicine, Greenville, North Carolina, USA.
Pratik Patel

Department of Gastroenterology, Mather Hospital/Hofstra University Zucker School of Medicine, New York City, New York, USA.
Dushyant Singh Dahiya

Division of Gastroenterology, Hepatology & Motility, The University of Kansas School of Medicine, Kansas City, Kansas, USA.
Manesh Kumar Gangwani

Department of Medicine, University of Toledo Medical Center, Toledo, Ohio, USA.
Debargha Basuli

Department of Internal Medicine, ECU health medical center/Brody School of Medicine, Greenville, North Carolina, USA.
Babu Pappu Mohan

Orlando Gastroenterology PA, Orlando, Florida, USA.

Keywords

Adult Age of Onset Colorectal Neoplasms Female Forecasting Humans Machine Learning Male Middle Aged United States Young Adult

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View on PubMed Access via DOI PubMed (38149332)

Prediction of early-onset colorectal cancer mortality rates in the United States using machine learning.

Abstract

Authors

Keywords

External Resources

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