Objectives Alzheimer’s disease (AD) poses a significant challenge for individuals aged 65 and older, being the most prevalent form of dementia. Although existing AD risk prediction tools demonstrate ...

Building a PC for AI or machine learning is very different from making your own gaming machine. Here are some top tips so you won't go wrong.

Differentiating Alzheimer’s disease from mild cognitive impairment: a quick screening tool based on machine learning ...

Risk management is relevant for every project that which seeks to avoid and suppress unanticipated costs, basically calling for pre-emptive action. The current work proposes a new approach for ...

In the rapidly evolving field of drug discovery, high-throughput screening (HTS) is essential for identifying bioactive compounds. This study introduces a novel application of data valuation, a ...

This systematic review and meta‐analysis compared the accuracies of prehospital stroke scales and machine learning models for detecting large vessel occlusion, offering novel insights into their ...

Enhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acute ischemic stroke appears promising. This systematic review explored the capabilities of ML models compared ...

With the advancement of science and technology, computational and machine learning (ML) methodologies provide a promising approach for analyzing high-dimensional data (8, 9). Recent applications of ML ...

Machine learning-based prediction has been effectively applied for many healthcare applications. Predicting breast screening attendance using machine learning (prior to the actual mammogram) is a new ...

Recent efforts have concentrated on training models that apply multimodal contrastive learning to map 2D chemical structures to high-content cell microscope pictures. In biotechnology, high-throughput ...

Data-driven machine learning is increasingly involved in human life and industrial development due to its large-scale testing and low time cost. However, existing learning algorithms are not suitable ...

2.5 Machine learning for screening candidate genes To identify the important biomarkers, candidate genes for the diagnosis of NAFLD with IS were further screened by using 3 machine-learning algorithms ...