AI Medical Compendium Topic

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Hospitals

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An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Distributed learning avoids problems associated with central data collection by training models locally at each site. This can be achieved by federated learning (FL) aggregating multiple models that were trained in parallel or training a s...

[The future patient monitoring in the bed ward].

Ugeskrift for laeger
Current monitoring of vital signs in hospital wards rely on infrequent manual measurements. This narrative review describes how new wearable devices with artificial intelligence interpretation may overcome this challenge by providing nurses with cont...

[Survey and analysis on digital construction of primary hospitals in Guizhou Province].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To investigate the utilization status and awareness of digital hospital construction among medical staff in critical care department of primary hospitals, so as to promote the process of digital medical health.

Hospital-Agnostic Image Representation Learning in Digital Pathology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference in procedures to acquire WSIs at various trial sites gives rise to variability in the histopathology images, thus making consistent diagnosis challeng...

Predicting Readmission Following Hospital Treatment for Patients with Alcohol Related Diagnoses in an Australian Regional Health District.

Studies in health technology and informatics
This study aims to investigate the prediction of hospital readmission of alcohol use disorder patients within 28 days of discharge and compare the performance of six machine learning methods i.e., random forest (RF), logistics regression, linear supp...

Deep Learning and Explainable Artificial Intelligence to Predict Patients' Choice of Hospital Levels in Urban and Rural Areas.

Studies in health technology and informatics
Maldistribution of healthcare resources among urban and rural areas is a significant challenge worldwide. People living in rural areas may have limited access to medical resources, and often neglect their health problems or receive insufficient care ...

Topic Modeling for International Patients' Consultations Using Natural Language Processing.

Studies in health technology and informatics
We extracted major topic by applying natural language processing and keyword extracting using TF, TF-IDF, TextRank, Yake, KeyBERT. 1452 consultation data were collected from the website and official hospital e-mail. We found six topics categorized in...

User Satisfaction with an AI System for Chest X-Ray Analysis Implemented in a Hospital's Emergency Setting.

Studies in health technology and informatics
The acceptance of artificial intelligence (AI) systems by health professionals is crucial to obtain a positive impact on the diagnosis pathway. We evaluated user satisfaction with an AI system for the automated detection of findings in chest x-rays, ...

Machine learning to predict passenger mortality and hospital length of stay following motor vehicle collision.

Neurosurgical focus
OBJECTIVE: Motor vehicle collisions (MVCs) account for 1.35 million deaths and cost $518 billion US dollars each year worldwide, disproportionately affecting young patients and low-income nations. The ability to successfully anticipate clinical outco...

Rapid SARS-CoV-2 Inactivation in a Simulated Hospital Room Using a Mobile and Autonomous Robot Emitting Ultraviolet-C Light.

The Journal of infectious diseases
The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since 2019 has made mask-wearing, physical distancing, hygiene, and disinfection complementary measures to control virus transmission. Especially for health facilities, we eva...