PURPOSE: Screening for diabetic retinopathy (DR) by ophthalmologists is costly and labour-intensive. Artificial Intelligence (AI) for automated DR detection could be a clinically and economically alternative. We assessed the performance of a confocal...
Neural networks : the official journal of the International Neural Network Society
Aug 7, 2024
Multiview learning (MVL) seeks to leverage the benefits of diverse perspectives to complement each other, effectively extracting and utilizing the latent information within the dataset. Several twin support vector machine-based MVL (MvTSVM) models ha...
Interdisciplinary sciences, computational life sciences
Aug 7, 2024
The exploration of the interactions between diseases and metabolites holds significant implications for the diagnosis and treatment of diseases. However, traditional experimental methods are time-consuming and costly, and current computational method...
OBJECTIVE: We used machine learning to develop and validate a multivariable algorithm allowing the accurate and early prediction of postoperative hypocalcemia risk.
Journal of chemical information and modeling
Aug 7, 2024
Room-temperature ferromagnets are high-value targets for discovery given the ease by which they could be embedded within magnetic devices. However, the multitude of potential interactions among magnetic ions and their surrounding environments renders...
Journal of chemical information and modeling
Aug 7, 2024
Thrombocytopenia, which is associated with thrombopoietin (TPO) deficiency, presents very limited treatment options and can lead to life-threatening complications. Discovering new therapeutic agents against thrombocytopenia has proven to be a challen...
Antimicrobial resistance and infection control
Aug 7, 2024
BACKGROUND: Nosocomial infections (NIs) frequently occur and adversely impact prognosis for hospitalized patients with cirrhosis. This study aims to develop and validate two machine learning models for NIs and in-hospital mortality risk prediction.
PURPOSE: Convolutional Neural Networks (CNNs) have emerged as transformative tools in the field of radiation oncology, significantly advancing the precision of contouring practices. However, the adaptability of these algorithms across diverse scanner...
Accurately assigning standardized diagnosis and procedure codes from clinical text is crucial for healthcare applications. However, this remains challenging due to the complexity of medical language. This paper proposes a novel model that incorporate...
Animal behavior is a critical aspect for a better understanding and management of animal health and welfare. The combination of cameras with artificial intelligence holds significant potential, particularly as it eliminates the need to handle animals...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.