Practice Management

Information Technology

Latest AI and machine learning research in information technology for healthcare professionals.

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Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction.

Heart failure is a leading cause of premature death, especially among individuals with a sedentary l...

EHR-ML: A data-driven framework for designing machine learning applications with electronic health records.

OBJECTIVE: The healthcare landscape is experiencing a transformation with the integration of Artific...

Discovering patient groups in sequential electronic healthcare data using unsupervised representation learning.

INTRODUCTION: Unsupervised feature learning methods inspired by natural language processing (NLP) mo...

Voice EHR: introducing multimodal audio data for health.

INTRODUCTION: Artificial intelligence (AI) models trained on audio data may have the potential to ra...

Enhanced Phenotype Identification of Common Ocular Diseases in Real-World Datasets.

OBJECTIVE: For studies using real-world data, accurately identifying patients with phenotypes of int...

Generative adversarial local density-based unsupervised anomaly detection.

Anomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense,...

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.

BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with typ...

Stacking Ensemble Deep Learning for Real-Time Intrusion Detection in IoMT Environments.

The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling advanced patient car...

Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.

Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent ...

Classifying Unstructured Text in Electronic Health Records for Mental Health Prediction Models: Large Language Model Evaluation Study.

BACKGROUND: Prediction models have demonstrated a range of applications across medicine, including u...

Piloting an automated query and scoring system to facilitate APDS patient identification from health systems.

INTRODUCTION: Patients with activated PI3Kδ syndrome (APDS) may elude diagnoses for nearly a decade....

Identification of an ANCA-associated vasculitis cohort using deep learning and electronic health records.

BACKGROUND: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identif...

The promise of AI in healthcare: transforming communication and decision-making for patients.

By addressing communication gaps, the integration of AI tools in healthcare has a greater ability to...

Investigating the performance of multivariate LSTM models to predict the occurrence of Distributed Denial of Service (DDoS) attack.

In the current cybersecurity landscape, Distributed Denial of Service (DDoS) attacks have become a p...

Neurological history both twinned and queried by generative artificial intelligence.

BACKGROUND AND OBJECTIVES: We propose the use of GPT-4 to facilitate initial history-taking in neuro...

Classification performance and reproducibility of GPT-4 omni for information extraction from veterinary electronic health records.

Large language models (LLMs) can extract information from veterinary electronic health records (EHRs...

The Role of Artificial Intelligence in Health Care.

Artificial intelligence (AI) plays a leading role in transmuting the field of healthcare. Numerous a...

Homo Sapiens Chromosomal Location Ontology: A Framework for Genomic Data in Biomedical Knowledge Graphs.

The Homo sapiens Chromosomal Location Ontology (HSCLO) is designed to facilitate the integration of ...

Generative artificial intelligence in graduate medical education.

Generative artificial intelligence (GenAI) is rapidly transforming various sectors, including health...

Harnessing NLP to investigate biomarker interactions and CVD risks in elderly chronic kidney disease patients.

Chronic kidney disease (CKD) significantly increases the risk of CVD diseases, particularly among el...

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