Artificial intelligence in cancer-related malnutrition and cachexia: a transformative tool in clinical nutrition
- PMID: 40374013
- PMCID: PMC12281514
- DOI: 10.1016/j.advnut.2025.100447
Artificial intelligence in cancer-related malnutrition and cachexia: a transformative tool in clinical nutrition
Conflict of interest statement
Conflict of interest The author reports no conflicts of interest.
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- doi: 10.1016/j.advnut.2025.100438
References
-
- Xu J., Jie Y., Sun Y., Gong D., Fan Y. Association of Global Leadership Initiative on Malnutrition with survival outcomes in patients with cancer: a systematic review and meta-analysis. Clin. Nutr. 2022;41(9):1874–1880. - PubMed
-
- Matsui R., Rifu K., Watanabe J., Inaki N., Fukunaga T. Impact of malnutrition as defined by the GLIM criteria on treatment outcomes in patients with cancer: a systematic review and meta-analysis. Clin. Nutr. 2023;42(5):615–624. - PubMed
-
- Groarke J.D., Crawford J., Collins S.M., Lubaczewski S., Roeland E.J., Naito T., et al. Ponsegromab for the treatment of cancer cachexia. N. Engl. J. Med. 2024;391(24):2291–2303. - PubMed
-
- Arends J., Bachmann P., Baracos V., Barthelemy M., Bertz H., Bozzetti K., et al. ESPEN guidelines on nutrition in cancer patients. Clin. Nutr. 2017;36(1):11–48. - PubMed
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