The Lancet

Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA…

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
PharmTech

AI-Powered Digital Twins Achieve High Accuracy in Human Lung Function Forecasting

Ex vivo lung perfusion (EVLP) provides a platform for testing therapies but faces challenges in standardizing drug evaluation. At AAPS PharmSci 360, Xuanzi Zhou says digital twins accurately predict ...
Study Finds on MSN

Scientists Develop Lung Cancer ‘Breathalyzer’ Test That Screens For Disease In Seconds

In A Nutshell A handheld breath sensor read eight chemicals and flagged lung cancer risk in a 67-person study. Accuracy was ...
Journal of Medical Internet Research

Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study

The gradient boosting machine followed closely with AUROC scores of 0.802 (95% CI 0.667-0.857) for the training dataset and 0.689 (95% CI 0.596-0.733) for the validation dataset. In contrast, both XGB ...
IEEE

Enhancing Predictive Accuracy of LSTM Neural Networks for Diabetes Risk through K-Fold Cross-Validation: Comparison with K-Nearest Neighbors and Expert Systems

Abstract: Diabetes is a metabolic disease with a rapidly increasing prevalence worldwide. Developing accurate diabetes risk prediction methods is crucial to enable earlier intervention and optimize ...
IEEE

Integrating K-Fold Cross-Validation with Advanced Classification Techniques for Shrub Coverage Mapping in Fire-Prone Landscapes using Sentinel-2 Imagery

Abstract: This study employs state of the art classification techniques, Support Vector Machine (SVM), Artificial Neural Network (ANN), and Random Forest (RF), to map shrub coverage in a fire-prone ...