Hospital-Based Medicine

Surveillance

Latest AI and machine learning research in surveillance for healthcare professionals.

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Showing 190-210 of 7,437 articles
AI for glaucoma, Are we reporting well? a systematic literature review of DECIDE-AI checklist adherence.

BACKGROUND/OBJECTIVES: This systematic literature review examines the quality of early clinical eval...

Redefining prostate cancer care: innovations and future directions in active surveillance.

PURPOSE OF REVIEW: This review provides a critical analysis of recent advancements in active surveil...

Of Lyme disease and machine learning in a One Health world.

OBJECTIVE: Lyme disease is a vector-borne emerging zoonosis in Ontario driven by human population gr...

Artificial intelligence for direct-to-physician reporting of ambulatory electrocardiography.

Developments in ambulatory electrocardiogram (ECG) technology have led to vast amounts of ECG data t...

ADR-DQPU: A Novel ADR Signal Detection Using Deep Reinforcement and Positive-Unlabeled Learning.

The medical community has grappled with the challenge of analysis and early detection of severe and ...

Exploration of the optimal deep learning model for english-Japanese machine translation of medical device adverse event terminology.

BACKGROUND: In Japan, reporting of medical device malfunctions and related health problems is mandat...

A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.

Accurate, real-time forecasts of influenza hospitalizations would facilitate prospective resource al...

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

BACKGROUND: Mumps is a viral respiratory disease characterized by facial swelling and transmitted th...

Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data.

Regarding the transportation of people, commodities, and other items, aeroplanes are an essential ne...

Around the EQUATOR With Clin-STAR: AI-Based Randomized Controlled Trial Challenges and Opportunities in Aging Research.

The CONSORT 2010 statement is a guideline that provides an evidence-based checklist of minimum repor...

Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques.

In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and ma...

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.

BACKGROUND: Controlling re-emerging outbreaks such as COVID-19 is a critical concern to global healt...

Machine learning web application for predicting varicose veins utilizing global prevalence data.

AimThis study aimed to develop a web-based machine learning (ML) model to predict the lifetime likel...

Pathogen genomic surveillance and the AI revolution.

The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveill...

Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.

DESCRIPTION: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of t...

Digital framework for georeferenced multiplatform surveillance of banana wilt using human in the loop AI and YOLO foundation models.

Bananas (Musa spp.) are a critical global food crop, providing a primary source of nutrition for mil...

Multi-Branch CNN-LSTM Fusion Network-Driven System With BERT Semantic Evaluator for Radiology Reporting in Emergency Head CTs.

The high volume of emergency room patients often necessitates head CT examinations to rule out ische...

Using machine learning to forecast peak health care service demand in real-time during the 2022-23 winter season: A pilot in England, UK.

During winter months, there is increased pressure on health care systems in temperature climates due...

A deep learning pipeline for systematic and accurate vertebral fracture reporting in computed tomography.

AIM: Spine fractures are a frequent and relevant diagnosis, but systematic documentation is time-con...

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