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Updates every hour. Last Updated: 21-Oct-2026 07:16 ET (21-Oct-2026 11:16 GMT/UTC)
Study proposes an explainable machine-learning framework for mortality risk in liver-transplant candidates with HCC
Health Data ScienceThis study proposes a framework combining LightGBM, SHAP, and supervised clustering for mortality-risk assessment among liver-transplant candidates with HCC. Eight SHAP-selected variables and supervised clustering identified seven subgroups with increasing risk levels.
The work offers a method for modeling the dual risks of liver dysfunction and tumor progression, but it does not establish that the model improves clinical decisions or patient outcomes.
- Journal
- Health Data Science
Better together: uniting experiments and models to predict ecosystems under global change
Institute of Botany, Chinese Academy of Sciences- Journal
- Journal of Plant Ecology
Can AI help make medical records less biased? New study suggests yes—with caveats
George Mason University- Journal
- JAMIA Open
[Research Article] An LLM-based multi-agent system for remote sensing analysis
Big Earth Data- Journal
- Big Earth Data
Research identifies farming practices that improve irrigation efficiency
Mississippi State University- Journal
- Agricultural Water Management
- Funder
- Agricultural Research Service
Hanyang University researchers achieve controllable doping in organic semiconductors
Hanyang University Research Strategy Planning TeamLewis-paired dopants are a promising way to achieve strong, stable doping in organic semiconductors, but their high reactivity makes precise control over doping levels difficult. In a recent study, researchers from Korea tackled this issue by showing that solvent polarity can regulate dopant reactivity during processing. Using this new strategy, they achieved finely tunable, efficient, and stable doping across multiple organic semiconductors, supporting the development of next-generation flexible and sustainable organic electronics.
- Journal
- Advanced Materials
A Pusan National University study explores the meaning of creativity in AI in the novel Ada
Pusan National University- Journal
- French Forum
Superior F1-score: I/O feature driven algorithms for stream computing systems workload identification
Higher Education PressStream computing systems are critical platforms for real-time processing and analysis of data streams, widely applied in handling diverse workloads from Kubernetes, Apache Kafka, and web services. However, as workload types increase and hardware environments become more complex, resource management faces rising challenges in meeting service quality, load management, elasticity, and cost-efficiency requirements.
- Journal
- Frontiers of Computer Science