Prescriptions

Personalizing Responsive Neurostimulation for Epilepsy.

Over the past 20 years, responsive neurostimulation (RNS), a closed-loop device for treating certain forms of drug-resistant focal epilepsy, has become ensconced in the epileptologist's therapeutic armamentarium. Through neuromodulatory effects, RNS therapy gradually reduces seizures over years, providing diagnostically valuable intracranial recordings along the way. However, the neuromodulatory p...

MSFCL: Drug Combination Risk Level Prediction Based on Multi-Source Feature Fusion and Contrastive Learning.

Accurate assessment of drug combination risk levels is crucial for guiding rational clinical medication and avoiding adverse reactions. However, most existing methods are limited to binary classification, which fails to quantify distinctions between risk levels and struggles with imbalanced data distribution and insufficient semantic alignment of heterogeneous features. To address these challenges...

Graph_RG: Dominating CASP16's Small Molecule Affinity Prediction Subcategory-A Pose-Free Framework for Billion-Scale Virtual Screening.

Protein-ligand interaction prediction is pivotal in early-stage drug development, enabling large-scale virtual screening, drug optimization, and rever...

Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis.

BACKGROUND: Digital mental health tools promise to enhance the reach and quality of care. Current tools often recommend content to individuals, typica...

Multi-factor interaction perspective: machine learning-based analysis of Ni⁺ adsorption onto soil.

With the rapid development of industry and agriculture, the ecological and health impacts of nickel (Ni) have gained increasing attention. While previ...

Seminars in epileptology: How to diagnose status epilepticus in adults and children.

Status epilepticus (SE) can be regarded as the most severe expression of seizure activity characterized by a low probability of spontaneous cessation ...

Improved Prediction of Drug-Protein Interactions through Physics-Based Few-Shot Learning.

Accurate prediction of drug-protein interactions is crucial for drug discovery. Due to the bottleneck of traditional scoring functions, many machine l...

Will the inclusion of AI anchors enhance the operational performance of live streaming e-commerce supply chains?

With the rapid growth of the live streaming e-commerce market, traditional live streaming models are encountering mounting challenges, whereas the adv...

Identifying Risk Factors of Substance Use in Finland: A Machine Learning Approach.

: This study explores the dynamics of substance use in Finland, employing Artificial Intelligence (AI) and Machine Learning techniques to identify key...

Next-generation cancer therapeutics: unveiling the potential of liposome-based nanoparticles through bioinformatics.

Cancer remains one of the most deadly diseases in the world, requiring constant growth and improvements in therapeutic strategies. Traditional cancer ...

Recent advances in deep learning for protein-protein interaction: a review.

Deep learning, a cornerstone of artificial intelligence, is driving rapid advancements in computational biology. Protein-protein interactions (PPIs) a...

Quantum-inspired computational drug design for phytopharmaceuticals: a herbal holography analysis.

CONTEXT: Modern medication discovery is undergoing a paradigm change at the junction of herbal pharmacology with computational modeling informed by qu...

Building Explainable Graph Neural Network by Sparse Learning for the Drug-Protein Binding Prediction.

Explainable Graph Neural Networks have been developed and applied to drug-protein binding prediction to identify the key chemical structures in a drug...

AI-Supported Documentation and Clinical Monitoring in Palliative Care: A Real-World Observational Study.

BackgroundPatients in palliative care often experience prolonged hospital stays, requiring detailed documentation, complex symptom management, and mul...

Patterns of calcitonin gene-related peptide monoclonal antibody use in people with migraine: Results of the OVERCOME (US) study.

BackgroundUnderstanding characteristics and reasons associated with using calcitonin gene-related peptide monoclonal antibodies (CGRP mAb) for migrain...

Artificial Intelligence in Chronic Disease Management for Aging Populations: A Systematic Review of Machine Learning and NLP Applications.

As China's elderly population grows rapidly and the aging society arrives, the number of elderly patients with chronic diseases (mainly including chro...

Gene as a Molecular Target Potentially Shared by Idiopathic Pulmonary Fibrosis and Pulmonary Hypertension: Drug Repurposing Prospect with Aminoglutethimide.

Idiopathic pulmonary fibrosis (IPF) and pulmonary hypertension (PH) are two chronic conditions that can coexist occasionally, resulting in high morbid...

Exploring the role of density functional theory in the design of gold nanoparticles for targeted drug delivery: a systematic review.

CONTEXT: Targeted drug delivery systems leveraging gold nanoparticles (AuNPs) demand precise atomic-level design to overcome current limitations in dr...

SCATrans: semantic cross-attention transformer for drug-drug interaction predication through multimodal biomedical data.

Predicting potential drug-drug interactions (DDIs) from biomedical data plays a critical role in drug therapy, drug development, drug regulation, and ...

A computational framework for longitudinal medication adherence prediction in breast cancer survivors: A social cognitive theory based approach.

Non-adherence to medications is a critical concern since nearly half of patients with chronic illnesses do not follow their prescribed medication regi...