Information Technology

Machine learning-based prediction of short-term recurrence of colorectal adenomatous polyps following EMR: model development and validation study.

OBJECTIVE: This study aims to develop and validate a model for predicting the 1-year recurrence of adenomatous polyps following endoscopic mucosal resection (EMR), and explore associated risk factors. METHODS: Patients who underwent their first EMR for colorectal polyps at the Affiliated Hospital of Xuzhou Medical University from September 2018 to September 2023 were retrospectively enrolled. The ...

GA-ConvE: An APT attack prediction method based on combination of graph attention network and 2D convolution.

APT (Advanced Persistent Threat) attacks have become a significant challenge in the field of cybersecurity. Timely and accurate identification and prediction of APT attacks are crucial tasks. This paper proposes a new APT attack prediction method-GA-ConvE. By collecting APT threat intelligence and constructing an attack behavior knowledge graph, we classify and infer similar APT behaviors from a k...

Early clinical implementation and evaluation of an NLP-Based AI system for thrombophilia assessment using electronic health records.

BACKGROUND: Thrombophilia evaluation requires integration of biochemical findings with clinical history, much of which is embedded in unstructured ele...

Artificial intelligence in clinical trials: A comprehensive review of opportunities, challenges, and future directions.

BACKGROUND: Clinical trials face unprecedented challenges including recruitment delays affecting 80% of studies, escalating costs exceeding $200 billi...

Innovative Approaches to Head and Neck Cancer Diagnosis.

Diagnosis, positioned between disease prevention and treatment, is essential for head and neck cancer management. Delays in diagnosis contribute to di...

Developing and Evaluating a Natural Language Processing Algorithm to Detect Insulin Pump and Continuous Glucose Monitor Use in Electronic Health Records of Patients with Type 1 Diabetes.

OBJECTIVE: We aimed to develop and validate natural language processing (NLP) algorithms to identify insulin pump and continuous glucose monitor (CGM)...

Democratizing AI in Healthcare with Open Medical Inference (OMI): Protocols, Data Exchange, and AI Integration.

The integration of artificial intelligence (AI) into healthcare is transforming clinical decision-making, patient outcomes, and workflows. AI inferenc...

AI in critical care: A roadmap to the future.

Artificial intelligence (AI) has the potential to revolutionize critical care medicine by enhancing patient care, improving resource allocation and re...

Enhancing risk stratification for incident systolic heart failure through machine learning and natural language processing.

BACKGROUND: Clinical guidelines advocate use of validated risk models in patients experiencing heart failure with reduced ejection fraction (HFrEF) to...

Global Trends and Emerging Themes in Tele-Ophthalmology Research: A Bibliometric Analysis (1993 to 2024).

BACKGROUND: Tele-ophthalmology is transforming eye care delivery, particularly in remote and underserved areas, where specialist shortages and geograp...

From promise to practice: A roadmap for artificial intelligence in critical care.

Artificial intelligence (AI) has regained strong momentum in medicine, driven by unprecedented computing power and the availability of massive clinica...

Utilization of an Artificial Intelligence-Based Documentation System Improves Provider Efficiency in Outpatient Orthopaedic Clinics: Reducing the Afterhours Burden of the Electronic Health Record-A Pilot Study.

INTRODUCTION: Despite recent technological advancements, documentation within the electronic health record (EHR) remains a time-consuming task within ...

Artificial intelligence and infectious disease diagnostics: state of the art and future perspectives.

Artificial intelligence (AI) is reshaping infectious disease diagnostics by supporting clinical decision making, optimising laboratory and clinical wo...

Interpretable Semi-federated Learning for Multimodal Cardiac Imaging and Risk Stratification: A Privacy-Preserving Framework.

The growing heterogeneity of cardiac patient data from hospitals and wearables necessitates predictive models that are tailored, comprehensible, and s...

Assessment of Multimodal Natural Language Processing in Ascertaining Perioperative Safety Indicators From Preoperative Notes in Spine Surgery.

INTRODUCTION: Standard spine surgery machine learning (ML) models often rely on structured clinical data, overlooking nuanced free text, such as preop...

The Case for the Pediatric Cardiologist-Informaticist.

One of the most ubiquitous and profound impacts to the delivery of healthcare over the last three decades has been the introduction of digital technol...

Flexible wearable medical devices: from material innovations and data processing to intelligent healthcare applications.

BACKGROUND: Flexible wearable medical devices drive healthcare transformation via non-invasive, real-time physiological monitoring and personalized ma...

Enhancing mechanical ventilation management with AI: Computer vision for automated detection of ventilatory modes, parameters and asynchrony.

PURPOSE: To evaluate the performance of an artificial intelligence (AI)-based decision support platform called NexoVent, which uses computer vision to...

Artificial Intelligence in Anterior Cruciate Ligament Tear Diagnosis: A Bibliometric Analysis of the 50 Most Cited Studies.

INTRODUCTION: Since the 2000s, artificial intelligence (AI) publications in medicine have surged, particularly in orthopaedics and radiology. A key ar...

Navigating Medical Device Safety: Current Status, Challenges, and Future Regulatory Directions.

Medical devices are indispensable in modern healthcare. They enable the prevention, diagnosis, and treatment of diseases while enhancing patient outco...