Information Technology

Digital hypertension in 2024-2025: emerging evidence and future directions.

Recent advances in digital technology are remarkable, and they are driving profound transformations in healthcare and medical research. Within this context, digital hypertension has emerged as a multidisciplinary paradigm that integrates novel digital technologies into the prevention, diagnosis, and management of hypertension. Digital hypertension encompasses diverse domains such as advanced senso...

Development and validation of a neural network survival prediction model for ischemic heart disease.

BACKGROUND: Current risk prediction models for ischemic heart disease in clinical use are relatively simple and use a limited collection of well-known risk factors. Using machine learning to integrate a broader panel of features from electronic health records (EHRs) may improve post-angiography prognostication. METHODS: This retrospective model development and validation study was based on Danish ...

Implementing an Artificial Intelligence Decision Support System in Radiology: Prospective Qualitative Evaluation Study Using the Nonadoption Abandonment Scale-Up, Spread, and Sustainability (NASSS) Framework.

BACKGROUND: Medical imaging remains at the forefront of advancements in adopting digital health technologies in clinical practice. Regulator-approved ...

Skin tone and clinical dataset from a prospective trial on acute care patients.

Although hypothesized to be the root cause of the pulse oximetry disparities, skin tone and its use for improving medical therapies have yet to be ext...

Implementation of electronic patient-reported outcomes in supportive care for oncology patients.

PURPOSE OF REVIEW: Patient-reported outcomes (PROs) have become increasingly important in oncology, capturing the patient perspective on symptoms, tre...

Integrated Health Technologies in Heart Failure: A Scientific Statement From the Heart Failure Society of America and the American Association of Heart Failure Nurses.

Integrated health technologies (IHTs) have emerged as promising tools for improving heart failure (HF) management by facilitating care coordination an...

IKDP: Implicit Knowledge Enhanced Disease Prediction via heterogeneous admission sequence graphs.

Despite significant advances in deep learning for electronic health record (EHR) modeling, accurately representing complex disease relationships and a...

Assessing Health Care Professionals' Perceptions of a New System in Clinical Workflows: Systems Engineering Initiative for Patient Safety-Based Consensual Qualitative Research.

BACKGROUND: Artificial intelligence (AI)-enabled clinical decision support systems (CDSSs) are increasingly embedded within electronic health record (...

Reproducing real-world clinical prediction models using the DIVE platform: A comparative validation study across three chronic diseases.

OBJECTIVES: The aim of this analysis is to evaluate the performance and reproducibility of the Python-based Data Insight Validation Engine (DIVE), a m...

Health Insurance Portability and Accountability Act Liability in the Age of Generative Artificial Intelligence.

As artificial intelligence tools become increasingly integrated into emergency department workflows, healthcare providers face a growing risk of legal...

[Telemedicine in heart failure : Evidence, benefits and future perspectives].

In recent years telemonitoring for heart failure (TmHi) has transitioned from project-based pilot applications to a structured and fully reimbursed co...

A Framework for Healthcare from the Eye: Oculomics as a Powerful Window to Systemic Health.

PURPOSE: To present a comprehensive framework for integrating oculomics to assess ocular and systemic health into coordinated health care delivery mod...

A comparative evaluation of handling missing data points and modalities in electronic health records.

BACKGROUND: Healthcare data, generally available as electronic health records (EHR), provide rich insights for predictive modelling. A common challeng...

Correction to: Deep learning prediction of steep and flat corneal curvature using fundus photography in post‑COVID telemedicine era.

Dual Ontology-enhanced Clinical Decision Learning for First-admission Mortality Prediction.

Time-series based deep learning methods have significantly improved performance of predictive healthcare tasks on electronic health records (EHR) data...

Enhanced language models for predicting and understanding HIV care disengagement: a case study in Tanzania.

Sustained engagement in HIV care and adherence to ART are crucial for meeting the UNAIDS "95-95-95" targets. Disengagement from care remains a signifi...

Subphenotype Identification for Sepsis-Associated Acute Kidney Injury Using Graph Bidirectional Mamba Networks.

Sepsis-associated acute kidney injury (SA-AKI) is a heterogeneous clinical syndrome and a leading cause of mortality in intensive care units (ICUs). I...

Clinically-guided models or foundation models? predicting cervical spondylotic myelopathy from electronic health records.

Cervical spondylotic myelopathy (CSM) is the leading cause of spinal cord dysfunction in older adults, yet diagnosis is frequently delayed due to insi...

Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach.

BACKGROUND: Changes in opioid prescribing practices have evolved, including perioperative settings. However, computerized clinical decision support sy...

Quantum-enhanced throughput pathways: Integrating Rodgers' TPM with quantum ethical frameworks for AI-driven cybersecurity.

This integrative conceptual review synthesizes psychological, ethical, and quantum-information perspectives to advance Quantum-Enhanced Throughput Mod...