Prescriptions

Variant calling in genomics: A comparative performance analysis and decision guide.

The accurate detection of genetic variants is critical for advancing genomics research and precision medicine. However, this task remains challenging due to pervasive sequencing errors and complex genomic regions. The choice of variant calling software significantly influences results, creating a need for clear, evidence-based guidance. This study aims to provide a performance evaluation and a cle...

Predicting the usage of seasonal drugs by utilizing advanced machine learning: An albuterol case study.

Manual forecasting of seasonal medication demand results in inefficiencies and labor burden. With the advancement of machine learning, there is an opportunity to develop a machine learning model that can predict the expected usage of medication for the next season by identifying patterns in usage data. This study aims to assess the application of a seasonal autoregressive integrated moving average...

Development and validation of a fentanyl quantification model for drug checking services.

BACKGROUND: Drug checking services are becoming increasingly popular. Despite the significant variability in fentanyl concentrations observed in the u...

Explainable AI reveals temporal risk pathways in fall prediction: Extracting clinical insights from multi-horizon machine learning models.

Falls are a leading cause of injury in older adults, making risk prediction a clinical priority. While many machine learning (ML) models exist, they t...

Patients' Attitudes and Beliefs Toward Artificial Intelligence Use in Cancer Care: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) is being rapidly integrated into oncologic care, yet little is known about how patients perceive these applic...

Protocol for Personalised Prediction of Persistent Postsurgical Pain.

INTRODUCTION: Persistent postsurgical pain (PPSP) affects up to 15% of patients after major surgery, impairing physical function, quality of life and ...

Applying biotechnology to overcome cancer drug resistance and improve public health outcomes.

This review examines how biotechnology advances (CRISPR/Cas9, next-generation targeted therapies, nanotechnology-based drug delivery, and immunotherap...

An IoT-based smart emotion recognition system by using internal body parameters.

Emotion recognition using physiological signals has gained significant attention in recent years due to its potential applications in mental health mo...

Validation of socialbit as a smartwatch algorithm for social interaction detection in a clinical population.

Social interaction supports brain health and recovery after neurological injury. Yet no validated tool exists for real-time measurement in individuals...

IIC-DTI: A Contrastive Learning Enhanced Inter-Intra Molecular Fusing Framework for Drug-Target Interaction Prediction.

PURPOSE: Predicting drug-target interactions (DTIs) is a practical demand in drug development and drug repositioning. Therefore, developing accurate a...

Knowledge-graph-enhanced multi-scale modeling for drug-drug interaction prediction.

Drug-drug interaction (DDI) prediction is crucial for understanding combined medication effects and preventing adverse reactions. Traditional machine ...

The Emerging Role of Artificial Intelligence in Drug Discovery and Development: Implications for Cardiovascular Pharmacology.

Cardiovascular diseases remain the leading cause of global morbidity and mortality, highlighting the urgent need for more efficient, precise, and cost...

Integrative Multiomics and Drug Sensitivity Profiling Reveal Potential Biomarkers and Therapeutic Strategies in Pediatric Solid Tumors.

UNLABELLED: Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. ...

Multi-omics integration in deciphering non-small cell lung cancer drug resistance: current status, challenges, and future prospects.

Lung cancer is the leading cause of cancer-related deaths globally. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung canc...

Transforming clinical toxicology in Singapore: four decades of progress and beyond.

By examining key milestones, challenges and future directions, this review chronicles the evolution of clinical toxicology in Singapore into a recogni...

Ensemble transfer learning for classifying physical examinations in GP consultation: a multi-model approach to human-object and human-to-human activity recognition.

OBJECTIVES: This study aims to automatically classify physical examinations performed during general practitioner (GP) consultations using a deep lear...

Mathematical and Artificial Intelligence Techniques in Modern Drug Discovery: A Review.

The future of drug research is intrinsically connected to the continuous advancement and prudent integration of Artificial intelligence (AI) and mathe...

Innovations to improve outcomes and uptake of psychotherapies for mental disorders: a state-of-the-art review.

Psychotherapies have been found effective in the treatment of most mental disorders. However, substantial improvements are still much needed, and many...

A Multimodal Multitask Artificial Intelligence Model for Orthokeratology Contact Lens Fitting: An Integrated Framework to Enhance Lens Centration and Myopia Control Effect.

PURPOSE: To develop a multimodal, multitask artificial intelligence (AI) model to classify postfitting corneal topography patterns and predict axial l...

Health trajectories of patients with amyotrophic lateral sclerosis before and after initiation of non-invasive ventilation: a French nationwide database analysis.

BACKGROUND: Management of amyotrophic lateral sclerosis (ALS) is complicated by heterogeneous presentation and unpredictable disease course. This stud...