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Latest AI and machine learning research in prescriptions for healthcare professionals.

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Traditional Methods Hold Their Ground Against Machine Learning in Predicting Potentially Inappropriate Medication Use in Older Adults.

OBJECTIVES: Machine learning methods have gained much attention in health sciences for predicting va...

Smart laser Sintering: Deep Learning-Powered powder bed fusion 3D printing in precision medicine.

Medicines remain ineffective for over 50% of patients due to conventional mass production methods wi...

Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI.

Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring both nu...

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across et...

Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review.

Artificial intelligence (AI) has played a vital role in computer-aided drug design (CADD). This deve...

Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population.

PURPOSE: This study aimed to develop a classifier using supervised machine learning to effectively a...

Virtual resonance: analyzing IPA usage intensity under COVID-19's isolating canopy.

The widespread adoption of smartphones coupled with advancements in artificial intelligence has sign...

Estimating substance use disparities across intersectional social positions using machine learning: An application of group-lasso interaction network.

OBJECTIVE: An aim of quantitative intersectional research is to model the joint impact of multiple s...

Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction.

BACKGROUND AND AIMS: Computer-aided diagnosis (CADx) for the optical diagnosis of colorectal polyps ...

Machine learning in drug delivery.

For decades, drug delivery scientists have been performing trial-and-error experimentation to manual...

DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.

Artificial intelligence (AI)-aided drug design has demonstrated unprecedented effects on modern drug...

The Role of AI in Drug Discovery.

The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceuti...

TransfIGN: A Structure-Based Deep Learning Method for Modeling the Interaction between HLA-A*02:01 and Antigen Peptides.

The intricate interaction between major histocompatibility complexes (MHCs) and antigen peptides wit...

Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery.

Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a pro...

Improved classification of soil As contamination at continental scale: Resolving class imbalances using machine learning approach.

The identification of arsenic (As)-contaminated areas is an important prerequisite for soil manageme...

Advancing drug discovery with deep attention neural networks.

In the dynamic field of drug discovery, deep attention neural networks are revolutionizing our appro...

Machine learning for antidepressant treatment selection in depression.

Finding the right antidepressant for the individual patient with major depressive disorder can be a ...

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue char...

Protein-Protein Interaction Prediction via Structure-Based Deep Learning.

Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intel...

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