AI Medical Compendium Topic

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Hospitals

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OPTIMIZATION OF PRE-HOSPITAL FIRST AID MANAGEMENT STRATEGIES FOR PATIENTS WITH INFECTIOUS DISEASES IN HUIZHOU CITY USING DEEP LEARNING ALGORITHM.

Acta clinica Croatica
The aim of the study was to optimize the pre-hospital first aid management strategy for patients with infectious diseases in Huizhou city, which is expected to provide a basis for the epidemic prevention and control, to save lives, and increase the p...

Predicting stroke outcome: A case for multimodal deep learning methods with tabular and CT Perfusion data.

Artificial intelligence in medicine
MOTIVATION: Acute ischemic stroke is one of the leading causes of morbidity and disability worldwide, often followed by a long rehabilitation period. To improve and personalize stroke rehabilitation, it is essential to provide a reliable prognosis to...

[Application of Intelligent Logistics System Based on AGV Robot in Medical Consumables Management].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: Medical consumables are expensive, with numerous specifications and large usage, and traditional manual management models have certain drawbacks. Building an intelligent logistics management system to improve management level.

Synthetic Data Improve Survival Status Prediction Models in Early-Onset Colorectal Cancer.

JCO clinical cancer informatics
PURPOSE: In artificial intelligence-based modeling, working with a limited number of patient groups is challenging. This retrospective study aimed to evaluate whether applying synthetic data generation methods to the clinical data of small patient gr...

Exploring the Performance of an Artificial Intelligence-Based Load Sensor for Total Knee Replacements.

Sensors (Basel, Switzerland)
Using tibial sensors in total knee replacements (TKRs) can enhance patient outcomes and reduce early revision surgeries, benefitting hospitals, the National Health Services (NHS), stakeholders, biomedical companies, surgeons, and patients. Having a s...

Multimodal deep learning-based diagnostic model for BPPV.

BMC medical informatics and decision making
BACKGROUND: Benign paroxysmal positional vertigo (BPPV) is a prevalent form of vertigo that necessitates a skilled physician to diagnose by observing the nystagmus and vertigo resulting from specific changes in the patient's position. In this study, ...

A hybrid modeling framework for generalizable and interpretable predictions of ICU mortality across multiple hospitals.

Scientific reports
The development of reliable mortality risk stratification models is an active research area in computational healthcare. Mortality risk stratification provides a standard to assist physicians in evaluating a patient's condition or prognosis objective...

Deep learning model for personalized prediction of positive MRSA culture using time-series electronic health records.

Nature communications
Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA is crucial for optimizing antibiotic therapy. Our study introduced a deep learning model, PyTorch_E...

Diagnosis of retinal damage using Resnet rescaling and support vector machine (Resnet-RS-SVM): a case study from an Indian hospital.

International ophthalmology
PURPOSE: This study aims to address the challenge of identifying retinal damage in medical applications through a computer-aided diagnosis (CAD) approach. Data was collected from four prominent eye hospitals in India for analysis and model developmen...

The Future Role of Radiologists in the Artificial Intelligence-Driven Hospital.

Annals of biomedical engineering
Increasing population and healthcare costs make changes in the healthcare system necessary. This article deals with ChatGPT's perspective on the future role of radiologists in the AI-driven hospital. This perspective will be augmented by further cons...