Machine learning for predicting colon cancer recurrence.

Journal: Surgical oncology

PMID: 38688191

Abstract

INTRODUCTION: Colorectal cancer (CRC) is a global public health concern, ranking among the most commonly diagnosed malignancies worldwide. Despite advancements in treatment modalities, the specter of CRC recurrence remains a significant challenge, demanding innovative solutions for early detection and intervention. The integration of machine learning into oncology offers a promising avenue to address this issue, providing data-driven insights and personalized care.

Authors

Erkan Kayikcioglu

Department of Medical Oncology, Suleyman Demirel University, Isparta, Turkey. Electronic address: drerkankayikcioglu@gmail.com.
Arif Hakan Onder

Department of Medical Oncology, Health Sciences University Antalya Research and Training Hospital, Antalya, Turkey.
Burcu Bacak

Department of Medical Oncology, Suleyman Demirel University, Isparta, Turkey.
Tekin Ahmet Serel

Department of Urology, Suleyman Demirel University, Isparta, Turkey.

Keywords

Adult Aged Aged, 80 and over Colonic Neoplasms Female Follow-Up Studies Humans Machine Learning Male Middle Aged Neoplasm Recurrence, Local Prognosis Retrospective Studies Risk Factors

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View on PubMed Access via DOI PubMed (38688191)

Machine learning for predicting colon cancer recurrence.

Abstract

Authors

Keywords

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