Latest AI and machine learning research in prescriptions for healthcare professionals.
Graph neural networks (GNN) offer an alternative approach to boost the screening effectiveness in dr...
A bottleneck in the development of new anti-cancer drugs is the recognition of their mode of action ...
BACKGROUND: Mesial temporal sclerosis (MTS) is the most common pathology associated with drug-resist...
BACKGROUND: Chronic diseases are the leading cause of disability and death in the United States. Cli...
Neurodegenerative diseases (NDs) pose serious healthcare challenges with limited therapeutic treatme...
BACKGROUND: Repeated opioid exposure leads to a variety of physiologic adaptations that develop at d...
Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection...
The advent of artificial intelligence (AI) has catalyzed a profound transformation in the pharmaceut...
OBJECTIVES: This study aims to develop and validate a novel deep-learning model that predicts the se...
Molecular design of small-molecule inhibitors targeting programmed cell death-1 (PD-1)/programmed ce...
Lactobacillus delbrueckii subsp. bulgaricus (L. bulgaricus) and Streptococcus thermophilus (S. therm...
Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound i...
BACKGROUND: Electron backscattering coefficient and electron-stopping power are essential concepts i...
Machine learning is rapidly advancing the drug discovery process, significantly enhancing speed and ...
In this work, apple purees from different particle concentration and verifying in size were reconsti...
Drug-Target interaction (DTI) prediction, a transformative approach in pharmaceutical research, seek...
Digital health applications (apps) have been available on prescription since 2019 and offer a multit...
Identifying interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) provides a ne...
The SARS-CoV-2 outbreak highlights the persistent vulnerability of humanity to epidemics and emergin...
The concurrent use of multiple drugs may result in drug-drug interactions, increasing the risk of ad...
Accurate prediction of Drug-Target binding Affinity (DTA) is a daunting yet pivotal task in the sphe...