Prescriptions

Numerical Inverse Design of Patient-Specific Dental Implants: Accelerating FEA-Based Optimization via Evolutionary Neural Surrogates.

Mechanical complications in dental implantology often arise from a mismatch between standardized geometries and patient-specific anatomical constraints. While high-fidelity finite element analysis (FEA) is the gold standard for identifying these risks, its high computational cost creates a "bottleneck" that prevents its use in routine surgical planning. To develop a numerical inverse design framew...

Gallstone disease classification using SLOA-optimized CatBoost classifier with explainable AI.

Gallstones are small stones that form in the gallbladder. Around 80% of individuals with gallstones do not present any symptoms. Despite the high accuracy of image-based machine learning (ML) models in the detection of gallstones, less research has been carried out regarding tabular data. This paper has discussed a publicly available tabular dataset in order to study some predictive models to dete...

Does lens opacity matter? The effect of cataract on deep learning based cardiovascular disease risk scores from fundus photos.

PURPOSE: To investigate the effect of cataracts on a deep learning (DL) model for cardiovascular disease (CVD) risk prediction. METHODS: This retrospe...

AI-enhanced cardiac digital twins extend drug proarrhythmic risk assessment through experimental data uncertainty propagation and overdose exploration: A loperamide case study.

Drug-induced QT interval prolongation is a key biomarker of proarrhythmic risk and central to drug cardiac safety evaluation alongside in vitro assays...

Prevalence and Predictors of Non-Exclusive Breastfeeding at Hospital Discharge in Uruguay.

BACKGROUND: The prescription of infant formula during postpartum hospitalization is one of several factors that influence breastfeeding. RESEARCH AIMS...

Integrating handcrafted and deep learning MRI signatures: an interpretable framework for predicting chemotherapy benefit in glioma.

The molecular and spatial heterogeneity of gliomas severely limits accurate prediction of postoperative adjuvant chemotherapy efficacy, representing a...

PromptSE: drug side effect prediction with LLM-derived pharmacological representations.

Predicting drug-side effect associations is vital for drug discovery and patient safety. Accurate prediction requires high-quality representations of ...

AI image generation technology for visual communication design.

This study addresses two key challenges in applying artificial intelligence (AI) image generation to visual communication design: insufficient alignme...

Evaluating Elicit's systematic reviews workflow in an umbrella review on air pollution and acute lower respiratory infections: a methodological study for quality appraisal.

BACKGROUND: The exponential growth of scientific publications has increased the complexity of evidence synthesis. Systematic reviews remain essential ...

Automated evidence surveillance with AI-enabled preranking with cutoff in living guideline maintenance: a simulation study.

OBJECTIVES: Living guidelines are an emerging approach to ensure timely synthesis of the research evidence. However, pragmatic methods for maintenance...

Association between the development of sepsis and the BAR index in patients with acute pancreatitis: A retrospective investigation based on MIMIC-IV database.

Sepsis, as a severe complication of acute pancreatitis (AP), needs to be identified and treated as early as possible. The blood urea nitrogen-to-album...

Multi-task deep learning for sub-clinical screening of mood and sleep disturbances using physical activity biomarkers.

BACKGROUND: Sub-clinical screening for mood disorders and sleep disturbances remains challenging due to limited accessibility of mental health screeni...

How Advanced Artificial Intelligence Technologies Shape Drug-Drug and Drug-Target Interaction Modeling.

Drug molecular interactions, including drug-drug interactions (DDIs) and drug-target interactions (DTIs), are critical for drug discovery and clinical...

An integrated computational-experimental approach identifies Malate Synthase G as therapeutic target to disrupt carbon metabolism in chronic Pseudomonas aeruginosa infection.

Pseudomonas aeruginosa is a leading cause of nosocomial infections, particularly in individuals with a compromised immune system. Due to its strong ad...

GraFSyn: An Interpretable Deep Learning Framework for Anticancer Drug Synergy via Graphlet Fingerprints.

Predicting drug synergy is important for accelerating the discovery of effective anticancer combination therapies. Synergy intrinsically depends on th...

O²RDL-net for joint risk classification and delay forecasting in logistics systems using interaction amplified deep.

Transportation and logistics systems face frequent delays and operational risks due to congestion, human factors, and rapidly changing conditions. Pre...

New Frontiers of Drug Development Through the Use of New Approach Methodologies.

On November 2025, AAPS PharmSci 360 convened a symposium that included experts in the application of various types of New Approach Methodologies (NAMs...

Why are rural hospitals closing in the U.S.? Predictors identified using explainable machine learning.

OBJECTIVE: Rural hospital closures in the U.S. reduce access to essential healthcare services and worsen health and economic outcomes in rural communi...

Agentic Artificial Intelligence for the Automated Generation of Accurate Summary Podcasts of Radiology Research Papers.

OBJECTIVE: To evaluate whether a custom agentic artificial intelligence (AI) pipeline can overcome the limitations of general-purpose large language m...

Anisotropic Amorphization of Black Titania.

The amorphous-shell/crystalline-core architecture of black titania is central to its exceptional visible-light absorption and catalytic properties, ye...