Practice Management

PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data.

: Glaucoma (GL) classification is crucial for early diagnosis and treatment, yet relying solely on stand-alone models or International Classification of Diseases (ICD) codes is insufficient due to limited predictive power and inconsistencies in clinical labeling. This study aims to improve GL classification using stacked weight-based machine learning models. : We analyzed a subset of 33,636 partic...

Formative Research for the Development and Implementation of a Smartphone Application to Report Breaches to the International Code of Marketing of Breast-Milk Substitutes in Mexico.

Almost 40 years after the adoption of the International Code of Marketing of Breast-Milk Substitutes ('the Code') in Mexico, noncompliance persists. In other countries, smartphone applications for reporting Code noncompliance have proven effective. This study aimed to identify key features for the design of a public health surveillance app to monitor Code breaches and the barriers and facilitators...

Multitask learning model for predicting non-coding RNA-disease associations: Incorporating local and global context.

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are crucial non-coding RNAs involved in various diseases. Understanding these interactions is vi...

Identifying novel risk factors for aneurysmal subarachnoid haemorrhage using machine learning.

Aneurysmal subarachnoid haemorrhage (aSAH) is a type of stroke with high mortality and morbidity. This study aimed to identify novel aSAH risk factors...

How to leverage large language models for automatic ICD coding.

ICD coding, which involves assigning appropriate ICD codes to clinical notes, is essential for healthcare tasks such as health expense claims, insuran...

Circulating lncRNAs as biomarkers for severe dengue using a machine learning approach.

OBJECTIVES: Dengue virus (DENV) infection is a significant global health concern, causing severe morbidity and mortality. While many cases present as ...

GraphSleepFormer: a multi-modal graph neural network for sleep staging in OSA patients.

Obstructive sleep apnea (OSA) is a prevalent sleep disorder. Accurate sleep staging is one of the prerequisites in the study of sleep-related disorder...

Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease.

BACKGROUND: Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver di...

Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea.

BACKGROUND: Retinal vein occlusion (RVO) is a leading cause of vision loss globally. Routine health check-up data-including demographic information, m...

A compendium of human gene functions derived from evolutionary modelling.

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resour...

Adaptable graph neural networks design to support generalizability for clinical event prediction.

OBJECTIVE: While many machine learning and deep learning-based models for clinical event prediction leverage various data elements from electronic hea...

Classification patterns identification of immunogenic cell death-related genes in heart failure based on deep learning.

Heart failure (HF) is a complex and prevalent condition, particularly in the elderly, presenting symptoms like chest tightness, shortness of breath, a...

Active learning and margin strategies for arrhythmia classification in implantable devices.

BACKGROUND AND OBJECTIVES: The massive storage of cardiac arrhythmic episodes from Implantable Cardioverter Defibrillators (ICD) and the advent of new...

Application of Clinical Department-Specific AI-Assisted Coding Using Taiwan Diagnosis-Related Groups: Retrospective Validation Study.

BACKGROUND: The accuracy of the ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) procedure coding system (P...

Developing an ICD-10 Coding Assistant: Pilot Study Using RoBERTa and GPT-4 for Term Extraction and Description-Based Code Selection.

BACKGROUND: The International Classification of Diseases (ICD), developed by the World Health Organization, standardizes health condition coding to su...

PrediRep: Modeling hierarchical predictive coding with an unsupervised deep learning network.

Hierarchical predictive coding (hPC) provides a compelling framework for understanding how the cortex predicts future sensory inputs by minimizing pre...

A deep learning analysis for dual healthcare system users and risk of opioid use disorder.

The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Administration to implement opioid prescribing guidelines...

A Comparison of Prostate Cancer Screening Information Quality on Standard and Advanced Versions of ChatGPT, Google Gemini, and Microsoft Copilot: A Cross-Sectional Study.

PurposeArtificially Intelligent (AI) chatbots have the potential to produce information to support shared prostate cancer (PrCA) decision-making. Ther...

Large language models vs human for classifying clinical documents.

BACKGROUND: Accurate classification of medical records is crucial for clinical documentation, particularly when using the 10th revision of the Interna...

Phenotypic antibiotic resistance prediction using antibiotic resistance genes and machine learning models in Mannheimia haemolytica.

Mannheimia haemolytica is one of the most common causative agents of bovine respiratory disease (BRD); however, antibiotic resistance in this species ...