Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer
Abstract Background Skeletal muscle loss during treatment is associated with poor survival outcomes in patients with ovarian cancer. Although changes in muscle mass can be assessed on computed tomography (CT) scans, this labour‐intensive process can impair its utility in clinical practice. This stud...
Main Authors: | Wen‐Han Hsu, Ai‐Tung Ko, Chia‐Sui Weng, Chih‐Long Chang, Ya‐Ting Jan, Jhen‐Bin Lin, Hung‐Ju Chien, Wan‐Chun Lin, Fang‐Ju Sun, Kun‐Pin Wu, Jie Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2023-10-01
|
Series: | Journal of Cachexia, Sarcopenia and Muscle |
Subjects: | |
Online Access: | https://doi.org/10.1002/jcsm.13282 |
Similar Items
-
Multilayer Concept Drift Detection Method Based on Model Explainability
by: Haolan Zhang, et al.
Published: (2024-01-01) -
Long-term effects of particulate matter on incident cardiovascular diseases in middle-aged and elder adults: The CHARLS cohort study
by: Shiyun Lv, et al.
Published: (2023-09-01) -
Towards XAI agnostic explainability to assess differential diagnosis for Meningitis diseases
by: Aya Messai, et al.
Published: (2024-01-01) -
Exploring the Pedestrian Route Choice Behaviors by Machine Learning Models
by: Cheng-Jie Jin, et al.
Published: (2024-04-01) -
Development and validation of an interpretable radiomic nomogram for severe radiation proctitis prediction in postoperative cervical cancer patients
by: Chaoyi Wei, et al.
Published: (2023-01-01)