Identifying and Reporting Dependent Adult abuse

Sparse deconvolution of cell type medleys in spatial transcriptomics.

Mapping cell distributions across spatial locations with whole-genome coverage is essential for understanding cellular responses and signaling However, current deconvolution models aim to estimate the proportions of distinct cell types in each spatial transcriptomics spot by integrating reference single-cell data. These models often assume strong overlap between the reference and spatial datasets,...

Systematic Exploration of Hospital Cost Variability: A Conformal Prediction-Based Outlier Detection Method for Electronic Health Records.

Marked variability in inpatient hospitalization costs poses significant challenges to healthcare quality, resource allocation, and patient outcomes. Traditional methods like Diagnosis-Related Groups (DRGs) aid in cost management but lack practical solutions for enhancing hospital care value. We introduce a novel methodology for outlier detection in Electronic Health Records (EHRs) using Conformal ...

Insights Powered by Artificial Intelligence: Analyzing the Extent of Method Validation in Pesticide Residue Literature.

Validation of analytical methods to assess figures of merit and other key performance parameters is a fundamental requirement within the fitness-for-p...

The Current State of Artificial Intelligence on Detecting Pulmonary Embolism via Computerised Tomography Pulmonary Angiogram: A Systematic Review.

Pulmonary embolism (PE) is a life-threatening condition with significant diagnostic challenges due to high rates of missed or delayed detection. Comp...

HLN-DDI: hierarchical molecular representation learning with co-attention mechanism for drug-drug interaction prediction.

BACKGROUND: Accurate identification of drug-drug interactions (DDIs) is critical in pharmacology, as DDIs can either enhance therapeutic efficacy or t...

The effects of learning experience on college students' deep english learning: a study of the chain mediation effect of motivation and strategy.

This study focuses on the impact of learning experience on college students' deep learning of English and the chain-mediated effects of motivation and...

Efficiency and Quality of Generative AI-Assisted Radiograph Reporting.

IMPORTANCE: Diagnostic imaging interpretation involves distilling multimodal clinical information into text form, a task well-suited to augmentation b...

A Deep Learning-Based Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: Pilot Results for Evaluating Thyroid Malignancy in Pediatric Cohorts.

Artificial intelligence (AI) models have shown promise in predicting malignant thyroid nodules in adults; however, research on deep learning (DL) for...

An Appraisal of the Quality of Development and Reporting of Predictive Models in Spine Surgery.

Study DesignLiterature review.ObjectiveThe Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) st...

A general framework for governing marketed AI/ML medical devices.

This project represents the first systematic assessment of the US Food and Drug Administration's postmarket surveillance of legally marketed artificia...

Hierarchical Information-guided robotic grasp detection.

With the advancement of deep learning, robotic grasping has seen widespread application in fields, becoming a critical component in enhancing automati...

Learning double balancing representation for heterogeneous dose-response curve estimation.

Estimating the individuals' potential response to varying treatment doses is crucial for decision-making in areas such as precision medicine and manag...

Neuroimaging Characterization of Acute Traumatic Brain Injury with Focus on Frontline Clinicians: Recommendations from the 2024 National Institute of Neurological Disorders and Stroke Traumatic Brain Injury Classification and Nomenclature Initiative Imaging Working Group.

Neuroimaging screening and surveillance is one of the first frontline diagnostic tools leveraged in the acute assessment (first 24 h postinjury) of pa...

Developing a transparent reporting tool for AI-based diagnostic prediction models of disease and syndrome in Chinese medicine: a Delphi protocol.

INTRODUCTION: The application of artificial intelligence in diagnostic prediction models for diseases and syndromes in Chinese Medicine (CM) has been ...

Interobserver agreement between artificial intelligence models in the thyroid imaging and reporting data system (TIRADS) assessment of thyroid nodules.

BACKGROUND: As ultrasound (US) is the most accurate tool for assessing the thyroid nodule (TN) risk of malignancy (RoM), international societies have ...

Dual-Domain deep prior guided sparse-view CT reconstruction with multi-scale fusion attention.

Sparse-view CT reconstruction is a challenging ill-posed inverse problem, where insufficient projection data leads to degraded image quality with incr...

Multitask semantic change detection guided by spatiotemporal semantic interaction.

Semantic Change Detection (SCD) aims to accurately identify the change areas and their categories in dual-time images, which is more complex and chall...

The added value of artificial intelligence using Quantib Prostate for the detection of prostate cancer at multiparametric magnetic resonance imaging.

PURPOSE: Artificial intelligence (AI) has been proposed to assist radiologists in reporting multiparametric magnetic resonance imaging (mpMRI) of the ...

Improving Foundation Model for Endoscopy Video Analysis via Representation Learning on Long Sequences.

Recent advancements in endoscopy video analysis have relied on the utilization of relatively short video clips extracted from longer videos or million...

The Role of Large Language Models (LLMs) in Breast Imaging Today and in the Near Future.

This narrative review focuses on the integration of large language models (LLMs), such as GPT-4 and Gemini, into breast imaging. LLMs excel in underst...