Machine learning

Machine learning

Artificial Intelligence in Healthcare: Transfer Learning and Large Language Models Showcase Significant Developments

Research conducted at Sindh Madressatul Islam University has unveiled the substantial impact of Transfer Learning (TL) and large language models on the healthcare sector. The study demonstrates the applications of these models in medical diagnostics, patient services, and clinical process automation, highlighting their potential to boost accuracy and efficiency. However,

Machine learning

Sustainability Research Reveals Machine Learning's Potential in Optimizing Concrete Compressive Strength

Research conducted by the University of Toledo has demonstrated the efficacy of machine learning algorithms in predicting the compressive strength of sustainable concrete incorporating waste glass powder. The study employed six machine learning algorithms, including linear regression, elastic net regression, and support vector regressor, to analyze 187 sets of experimental

Machine learning

Artificial Intelligence Revolutionizes Medical Biostatistics: Implications for Personalized Medicine

Research conducted at the University of Medicine and Pharmacy has found that artificial intelligence (AI) techniques, such as deep learning, support vector machines, and decision trees, are expanding traditional biostatistics and enabling the processing of complex biomedical datasets. AI is transforming research methodologies in medical biostatistics, providing new tools for

Machine learning

Cardiosense's Noninvasive Sensor and AI Algorithm Succeeds in Estimating Cardiac Filling Pressure in Heart Failure Patients

A landmark study published in the Journal of the American College of Cardiology: Heart Failure demonstrates the efficacy of Cardiosense's novel machine learning algorithm in accurately estimating pulmonary capillary wedge pressure (PCWP) in patients with heart failure with reduced ejection fraction (HFrEF) using a noninvasive sensor. The prospective,