The efficient management of hospital resources, particularly in terms of bed utilisation and staff allocation, is increasingly critical in modern healthcare systems. Predictive modelling for hospital ...

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 ...

In-hospital outcomes of acute pulmonary embolism in patients with gastrointestinal cancer: A nationwide study. This is an ASCO Meeting Abstract from the 2024 ASCO Gastrointestinal Cancers Symposium.

DataZapp brings AI and machine learning to deliver affordable, predictive demand generation and marketing data for home ...

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

The Opioid Risk Tool for Opioid Use Disorder may help identify patients with chronic noncancer pain at increased risk for OUD ...

The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

Keysight Technologies has introduced a new Machine Learning Toolkit as part of its latest Device Modelling Software Suite, aiming to reduce the time required for semiconductor device modelling and ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...