News summary

Development and Validation of a Malnutrition Assessment Model for Patients with Liver Cirrhosis: An Interpretable Machine Learning Study

Source: Frontiers - Health • Published: 05 Nov 2026, 00:00

Summarized by Masters of Longevity from Frontiers - Health.

An RBF-SVM model using eight routine indicators predicted malnutrition in cirrhosis.

Development and Validation of a Malnutrition Assessment Model for Patients with Liver Cirrhosis: An Interpretable Machine Learning Study
Key Takeaways
  • Model was trained on hospitalized cirrhosis patients and validated temporally.
  • Temporal validation showed good discrimination with AUC of about 0.83.
  • Albumin, adjusted BMI, and AMC were the strongest model contributors.
Read the full article at Frontiers - Health ↗

Continue exploring

Recommended MoL Picks

MoL PickCan Doctors Be Trained for the Longevity Era?A new global survey suggests that healthy longevity medicine education can change how physicians think and talk about ageing. But the evidence also highlights how much work remains before a rapidly growing field becomes routine clinical care.MoL PickLongevity is leaving the clinicStephen Watson argues that hotels, gyms and residential communities can build longevity memberships around the relationships they already have.MoL PickMOTS-c: Where the Evidence EndsStudies offer clues about ageing and metabolism. What do they actually tell us about human health—and where does expert opinion take over?