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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

M. Santoni

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Review Sep 2026

Nutritional status and survival outcomes in patients with cancer treated with immune checkpoint inhibitors: The ARON-MOUSEION-20 systematic review and meta-analysis.

INTRODUCTION The prevalence of malnutrition in cancer patients is already high at diagnosis, reaching up to 40%, and tends to increase during treatment, affecting up to 75-80% of patients. To investigate the relationship between nutritional status and clinical outcomes, Progression-Free Survival (PFS) and Overall Survi...

Chiara Paciolla, E. Vitale, L. Maistrello et al. · 0 citations
Aug 2026

Machine learning-integrated explainable artificial intelligence for survival prediction in urothelial carcinoma with enfortumab vedotin: an exploratory real-world analysis.

BACKGROUND Enfortumab vedotin (EV) has transformed treatment for advanced urothelial carcinoma (aUC), but outcomes vary. Machine learning (ML) with explainable artificial intelligence (XAI) may improve survival prediction. METHODS Data from 544 aUC patients receiving EV after platinum chemotherapy and immunotherapy (...

K. Sridharan, O. Fiala, G. Sivaramakrishnan et al. · 0 citations
Review Open access Sep 2026

Liquid biopsy: a new window on the BRCA genes

Beyond the attractive potential to surrogate the tumor tissue testing, to overcome the cancer spatial and temporal heterogeneity, and to monitor the tumor mutational profile over time, accurately detecting all clinically relevant BRCA genetic variants and epigenetic modifications using LB remains technically challengin...

L. Incorvaia, V. Gristina, F. Pepe et al. · 0 citations
#explainable ai Sep 2026

Machine learning integrated explainable artificial intelligence in predicting toxicities of enfortumab vedotin in urothelial carcinoma: an exploratory study.

Preliminary, hypothesis-generating findings suggest ML may predict EV-related toxicities, but single train-test split, small event counts, and lack of external validation preclude clinical use.

K. Sridharan, Mattia Alberto Di Civita, G. Sivaramakrishnan et al. · 0 citations

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