Latest AI and machine learning research in prescriptions for healthcare professionals.
OBJECTIVE: To clinically validate a convolutional neural network (CNN)-based Android smartphone app ...
Discovering therapeutic molecules requires the integration of both phenotype-based drug discovery (P...
Drug repurposing identifies new therapeutic uses for the existing drugs originally developed for dif...
Whole-body bone scan (WBS) is usually used as the effective diagnostic method for early-stage and co...
Traditional Chinese Medicine (TCM) boasts a long history and a unique diagnostic and therapeutic par...
Investigating the inhibitory effects of compounds on cardiac ion channels is essential for assessing...
Molecular property prediction is a key component of AI-driven drug discovery and molecular character...
Exploring simple and efficient computational methods for drug repositioning has emerged as a popular...
Uncovering novel drug-drug interactions (DDIs) plays a pivotal role in advancing drug development an...
Solubility is not only a significant physical property of molecules but also a vital factor in small...
Predicting the binding affinity of drug target is essential to reduce drug development costs and cyc...
The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vit...
Drug repositioning greatly reduces drug development costs and time by discovering new indications fo...
Knowledge of unintended effects of drugs is critical in assessing the risk of treatment and in drug ...
Identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared t...
A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repu...
Drug repositioning has emerged as a promising strategy for identifying new therapeutic applications ...
Cancer is a multifaceted disease that results from co-mutations of multi biological molecules. A pro...
In breast diagnostic imaging, the morphological variability of breast tumors and the inherent ambigu...
Predicting the response of a cancer cell line to a therapeutic drug is pivotal for personalized medi...
Effect heterogeneity analyses using causal machine learning algorithms have gained popularity in rec...