Latest AI and machine learning research in prescriptions for healthcare professionals.
Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simul...
Structured claims or EMR datasets have limitations, such as lacking important clinical variables, upcoding, or potential coding errors. Unstructured data powered with natural language processing (NLP) might bridge these gaps. We assessed the integration of NLP with unstructured data in advancing care for rheumatoid arthritis (RA). We conducted a scoping literature review search in PubMed, Embase, ...
BACKGROUND: Clinical guidelines recommend a stepped-care strategy for patients with hip and knee osteoarthritis that begins with nonoperative approach...
Cancer remains a leading cause of mortality globally, with the incidence projected to reach 28.4 million new cases annually by 2040. Traditional drug ...
Joint music-making and conversation are two fundamental forms of human interaction. A growing number of hyperscanning studies have examined interperso...
BACKGROUND: Health technology assessment bodies increasingly emphasise the importance of preference-weighted health-related quality of life (HRQoL) ev...
This study investigates the direct effects and the interaction between green finance and technological innovation on China's economic growth. The empi...
Accurate prediction of drug-target binding affinity is central to computational drug discovery, yet it remains difficult because binding is governed b...
Breast density is a breast cancer risk factor. The accurate quantification of breast density requires reliable segmentation of dense tissue in mammogr...
BACKGROUND: To assess patient trust in AI-generated medication information, examine associated behavioral safety risks, and evaluate patient expectati...
Urban air pollution, specifically Nitrogen Dioxide (NO2), presents a multifaceted challenge that is intricately coupled with the stochastic, multi-mod...
Accurate prediction of drug-target interactions (DTIs) plays a crucial role in modern drug discovery and repositioning. Despite recent advances in dee...
Automatic picking of ginkgo fruits is beneficial for prolonging their freshness and ensuring quality during storage. Accurate identification of ginkgo...
Transcatheter Aortic Valve Replacement (TAVR) has emerged as a prominent, minimally invasive treatment for patients with severe aortic stenosis, a lif...
Drug-target interaction (DTI) prediction is vital for computer-aided drug discovery, yet current methods struggle with cross-domain generalization and...
For more than five decades, patients with the same condition have received markedly different care depending on which clinician they happen to see. Th...
Wind turbine blades are critical components of wind power systems, and early accurate detection of surface defects is essential for ensuring operation...
Homologous recombination deficiency (HRD) assays are used to select patients with ovarian cancer for PARP inhibitors, but they do not fully capture th...
Ion channels represent a crucial class of drug targets. Currently, with the structural elucidation of more and more ion channels and the rapid develop...
Many cancer monotherapies demonstrate limited clinical efficacy, making combination therapies a relevant treatment strategy. The extensive number of p...