AIMC Topic: Hospitals

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Machine learning vs. regression models to predict the risk of Legionella contamination in a hospital water network.

Annali di igiene : medicina preventiva e di comunita
INTRODUCTION: The periodic monitoring of Legionella in hospital water networks allows preventive measures to be taken to avoid the risk of legionellosis to patients and healthcare workers.

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...

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...

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...

Evaluating Natural Language Processing Packages for Predicting Hospital-Acquired Pressure Injuries From Clinical Notes.

Computers, informatics, nursing : CIN
Incidence of hospital-acquired pressure injury, a key indicator of nursing quality, is directly proportional to adverse outcomes, increased hospital stays, and economic burdens on patients, caregivers, and society. Thus, predicting hospital-acquired ...

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...

Virtual hospital and artificial intelligence: a first step towards the application of an innovative health system for the care of rare cerebrovascular diseases.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
The development of virtual care options, including virtual hospital platforms, is rapidly changing the healthcare, mostly in the pandemic period, due to difficulties in in-person consultations. For this purpose, in 2020, a neurological Virtual Hospit...