Product Alert

Periodontal bone loss analysis via keypoint detection with heuristic post-processing.

OBJECTIVES: This study proposes a deep learning framework and an annotation methodology for the automatic detection of periodontal bone loss landmarks, associated conditions, and staging. Methods192 periapical radiographs were collected and annotated using a stage agnostic methodology, labelling clinically relevant landmarks regardless of disease presence or extent. We propose a heuristic post-pro...

Artificial intelligence-driven predictive analytics for postoperative management and recovery in trauma patients.

PURPOSE OF REVIEW: Post-traumatic care is evolving from a reactive, protocol-driven paradigm to a predictive, personalized approach. This review examines how artificial intelligence and machine learning are redefining postoperative management by predicting complications before they manifest. RECENT FINDINGS: Recent literature (2023-2025) highlights three major advances: (a) the validation of gradi...

Exfoliated kidney cells from urine for non-invasive kidney transplant monitoring: A potential opportunity?

Kidney transplantation is usually the optimal treatment option for patients living with kidney failure given its associations with improved survival, ...

Early Prediction of Adverse Stroke Outcomes using Non-clinical Factors and Missing Data: A Machine Learning Study.

Introduction Early prediction of stroke outcomes using prognostic tools may help clinical decision making and inform resource allocation. However, cli...

Association of epicardial adipose tissue with markers of cardiac remodelling and clinical outcomes in asymptomatic aortic stenosis.

BACKGROUND: Previous studies have suggested an adverse role of epicardial adipose tissue (EAT) in aortic stenosis (AS), potentially mediated by direct...

Effects of Lactiplantibacillus plantarum on moderate dyslipidemia before medication involving gut microbiota and host genetics.

In this 12-week trial, 136 participants with moderately dyslipidemia were randomly assigned to receive Lactiplantibacillus plantarum (LP) or placebo. ...

Multimodal AI System for Plastic Surgery Diagnosis and Decision-Making Using Deep Learning of Psychological Questionnaires and Three-Dimensional Facial Data.

PURPOSE: To design and develop an AI-based plastic surgery recommendation system using 3D photographs and psychological questionnaire surveys, aiming ...

Structure-Based Prediction of QT Prolongation Risk Using Graph Neural Networks: An Integrative Approach Combining In Vitro hERG Assays and Pharmacovigilance Data.

Drug-induced QT-interval prolongation, a non-specific biomarker of increased risk for Torsades de Pointes (TdP), is a major safety concern in drug dev...

Theoretical and applied research on spatio-temporal graph attention networks for single-trial P300 detection.

Objective.Accurate detection of single-trial P300 ERPs (event-related potentials) is crucial for developing high-performance non-invasive BCIs (brain-...

How to predict abnormal acid reflux: recent developments.

INTRODUCTION: Recent advances in physiology and technology have led to the identification of additional parameters that have the potential to enhance ...

From black box to clear box: explainable AI for next-gen pharmacovigilance.

INTRODUCTION: Pharmacovigilance (PV) plays a vital role in post-marketing surveillance of drug safety; however, traditional methods are hindered by un...

Remote sensing analysis of forest fire impacts on ecosystem productivity, greenhouse gas emissions, and fire risk in Pakistan.

This study investigates the spatial variability of forest fire intensity, burn indices, ecosystem productivity, and Greenhouse Gas (GHG) emissions in ...

Developing and validating a machine learning model for predicting post-thrombolysis seizures in acute ischemic stroke.

Post-stroke seizures (PSS) manifests variably due to ischemic brain injury, yet its risk factors remain unclear. This study developed a machine learni...

A Review Exploring the Translational Perspective of Artificial Intelligence in Drug Discovery and Formulation Development.

The drug development pipeline remains extraordinarily complex, costly, and time-intensive, typically requiring 10-15 years and $2-3 billion per approv...

Nitrilotriacetic acid functionalized gold nanopillars enable stochastic detection and deep learning analysis of prolines and hydroxyprolines by surface enhanced Raman spectroscopy.

Proline hydroxylation is crucial for monitoring diseases related to collagen metabolism, analyzing metabolic pathways, and evaluating therapeutic or n...

Interpretable AI-driven prediction of early postoperative recurrence in locally advanced rectal cancer using the Systemic Inflammatory-Nutritional Index (SINTI): A multi-center study and clinical web tool.

BACKGROUND: Patients with locally advanced rectal cancer (LARC) who undergo neoadjuvant chemoradiotherapy (NCRT) and subsequently experience early rec...

Prior beliefs & automated fact checking: Limits on the effectiveness of AI-based corrections.

Proliferation of misinformation poses significant challenges in contemporary society, necessitating efficient strategies for its identification and mi...

Pioneering the future: Delivering the first digitally generated CMC post-approval change dossier to global regulators simultaneously.

As medicinal products and their manufacturing processes evolve, biopharmaceutical companies must continuously manage, document, and submit post-approv...

Exploratory identification of intestinal health and productive performance patterns in post-weaning piglets using explainable machine learning.

Weaning is a critical stage in swine production, characterized by intestinal alterations that affect piglet health and performance. In this study, mac...

Prognostic Significance of Lymph Node Ratio for Overall Survival in Patients with Lymph Node-Positive Bladder Cancer Post-Radical Cystectomy and Chemotherapy: A Multicenter Cohort Analysis.

BACKGROUND: The lymph node ratio (LNR) is gaining recognition as a prognostic biomarker for various malignant neoplasms. However, its prognostic role ...