Latest AI and machine learning research in prescriptions for healthcare professionals.
Artificial intelligence (AI) algorithms have been retrospectively evaluated as replacement for one r...
BACKGROUND: Unsupervised machine learning describes a collection of powerful techniques that seek to...
Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model i...
Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represen...
Human listeners have the ability to direct their attention to a single speaker in a multi-talker env...
Drug target interaction prediction is a crucial stage in drug discovery. However, brute-force search...
BACKGROUND: Pain is a complex subjective experience, strongly impacting health and quality of life. ...
This work proposes a convolutional neural network (CNN) that utilizes different combinations of para...
The rapid advancement of artificial intelligence (AI) in the 21st century is driving profound societ...
Inferring potential drug indications plays a vital role in the drug discovery process. It can be tim...
Accurate identification of bacterial strains in clinical samples is essential to provide an appropri...
BACKGROUND: Rehabilitation training based on the brain-computer interface of motor imagery (MI-BCI) ...
In recent years, the rapid advancement of generative artificial intelligence (GenAI) has revolutioni...
The interaction between microbes and drugs encompasses the sourcing of pharmaceutical compounds, mic...
Finding candidate molecules with favorable pharmacological activity, low toxicity, and proper pharma...
Drug-drug interactions (DDIs) trigger unexpected pharmacological effects in vivo, often with unknown...
Predicting drug-drug interactions (DDIs) is the problem of predicting side effects (unwanted outcome...
Deprescribing is an evidence-based intervention to reduce potentially inappropriate medication use. ...
Despite extensive efforts, current drug-delivery systems face biological barriers and difficulties i...
OBJECTIVES: To evaluate the FeelBetter machine learning system's ability to accurately identify olde...
INTRODUCTION: The accurate identification and timely updating of adverse reactions in drug labeling ...