Practice Management

Information Technology

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

7,403 articles
Stay Ahead - Weekly Information Technology research updates
Subscribe
Browse Specialties
Showing 274-294 of 7,403 articles
NSSC: a neuro-symbolic AI system for enhancing accuracy of named entity recognition and linking from oncologic clinical notes.

Accurate recognition and linking of oncologic entities in clinical notes is essential for extracting...

Leather-Based Shoe Soles for Real-Time Gait Recognition and Automatic Remote Assistance Using Machine Learning.

Real-time monitoring of gait characteristics is crucial for applications in health monitoring, patie...

Automated anonymization of radiology reports: comparison of publicly available natural language processing and large language models.

PURPOSE: Medical reports, governed by HIPAA regulations, contain personal health information (PHI), ...

Laboratory Data as a Potential Source of Bias in Healthcare Artificial Intelligence and Machine Learning Models.

Artificial intelligence (AI) and machine learning (ML) are anticipated to transform the practice of ...

Use of Deep Learning to Identify Peripheral Arterial Disease Cases From Narrative Clinical Notes.

INTRODUCTION: Peripheral arterial disease (PAD) is the leading cause of amputation in the United Sta...

Intelligent wearable-assisted digital healthcare industry 5.0.

The latest evolution of the healthcare industry from Industry 1.0 to 5.0, incorporating smart wearab...

ChatGPT-4 extraction of heart failure symptoms and signs from electronic health records.

BACKGROUND: Natural language processing (NLP) can facilitate research utilizing data from electronic...

Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?

In the last decades, clinical laboratories have significantly advanced their technological capabilit...

A Pragmatic Approach to Fetal Monitoring via Cardiotocography Using Feature Elimination and Hyperparameter Optimization.

Cardiotocography (CTG) is used to assess the health of the fetus during birth or antenatally in the ...

Controversies in Artificial Intelligence in Neurosurgery.

Artificial intelligence (AI) has evolved from science fiction to a technology infiltrating everyday ...

Applying machine learning approaches for predicting obesity risk using US health administrative claims database.

INTRODUCTION: Body mass index (BMI) is inadequately recorded in US administrative claims databases. ...

A novel approach for heart disease prediction using hybridized AITHO algorithm and SANFIS classifier.

In today's world, heart disease threatens human life owing to higher mortality and morbidity across ...

Prevention of adverse HIV treatment outcomes: machine learning to enable proactive support of people at risk of HIV care disengagement in Tanzania.

OBJECTIVES: This study aimed to develop a machine learning (ML) model to predict disengagement from ...

Identifying Facilitators and Barriers to Implementation of AI-Assisted Clinical Decision Support in an Electronic Health Record System.

Recent advancements in computing have led to the development of artificial intelligence (AI) enabled...

Criticality of Nursing Care for Patients With Alzheimer's Disease in the ICU: Insights From MIMIC III Dataset.

Alzheimer's disease (AD) patients admitted to intensive care units (ICUs) exhibit varying survival o...

Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing.

Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are gett...

Predicting hypoglycemia in ICU patients: a machine learning approach.

BACKGROUND: The current study sets out to develop and validate a robust machine-learning model utili...

Enhancing Cybersecurity in Healthcare: Evaluating Ensemble Learning Models for Intrusion Detection in the Internet of Medical Things.

This study investigates the efficacy of machine learning models for intrusion detection in the Inter...

An intrusion detection model to detect zero-day attacks in unseen data using machine learning.

In an era marked by pervasive digital connectivity, cybersecurity concerns have escalated. The rapid...

Browse Specialties