Interpretable machine learning model based on clinical factors for predicting muscle radiodensity loss after treatment in ovarian cancer
Author:
Funder
National Science and Technology Council
Mackay Memorial Hospital
Mackay Memorial Hospital,Taiwan
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00520-024-08757-z.pdf
Reference37 articles.
1. Jin Y, Ma X, Yang Z, Zhang N (2023) Low L3 skeletal muscle index associated with the clinicopathological characteristics and prognosis of ovarian cancer: a meta-analysis. J Cachexia Sarcopenia Muscle 14(2):697–705
2. McSharry V, Glennon K, Mullee A (2021) Brennan D (2021) The impact of body composition on treatment in ovarian cancer: a current insight. Expert Rev Clin Pharmacol 14:1–10
3. Pergialiotis V, Sotiropoulou IM, Liatsou E, Liontos M, Frountzas M, Thomakos N et al (2022) Quality of life of ovarian cancer patients treated with combined platinum taxane chemotherapy: a systematic review of the literature. Support Care Cancer 30(9):7147–7157
4. Huang CY, Yang YC, Chen TC, Chen JR, Chen YJ, Wu MH et al (2020) Muscle loss during primary debulking surgery and chemotherapy predicts poor survival in advanced-stage ovarian cancer. J Cachexia Sarcopenia Muscle 11(2):534–546
5. Rutten IJ, van Dijk DP, Kruitwagen RF, Beets-Tan RG, OldeDamink SW, van Gorp T (2016) Loss of skeletal muscle during neoadjuvant chemotherapy is related to decreased survival in ovarian cancer patients. J Cachexia Sarcopenia Muscle 7(4):458–466
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