Scientists from Malaysia and Thailand have developed a novel machine-learning model for predicting the maintenance needs of large-scale solar PV plants. According to a recently published scientific ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Dynamic prediction of cancer-associated thrombosis to guide prophylactic anticoagulation. Age distribution of metastatic cancer patients and chemotherapy discontinuation rates.

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...

The development of next-generation metallic materials is entering a transformative era driven by data-driven methodologies. Traditional trial-and-error ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

This studentship will develop physics-informed Edge AI methods for predictive health management of batteries and power electronics in electrified vehicles under real-world driving conditions.

Healthcare leaders have spent years trying to figure out how to manage the rising cost of aging, especially when it comes to ...