AIMC Topic: Hospitals

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Understanding what patients think about hospitals: A deep learning approach for detecting emotions in patient opinions.

Artificial intelligence in medicine
INTRODUCTION: Most hospital assessment systems are based on the study of objective statistical variables as well as patient opinions on their experiences with respect to the services offered by each hospital. Nevertheless, studies have indicated that...

Design and Implementation of Advanced Machine Learning Management and Its Impact on Better Healthcare Services: A Multiple Regression Analysis Approach (MRAA).

Computational and mathematical methods in medicine
In the current information and technology era, business enterprises are focusing in performing the process effectively by reducing the waiting time in completing the work, reduce latency and deploy the resources effectively so as to service the patie...

Factors associated with COVID-19 lethality in a hospital in the Cajamarca region in Peru.

Revista peruana de medicina experimental y salud publica
OBJECTIVE.: To identify the clinical and epidemiological characteristics related to lethality in patients hospitalized for COVID-19 at the Simón Bolívar Hospital in Cajamarca, during June-August 2020.

Implementation of Hospital-to-Home Model for Nutritional Nursing Management of Patients with Chronic Kidney Disease Using Artificial Intelligence Algorithm Combined with CT Internet.

Contrast media & molecular imaging
The objective of this study was to evaluate the application value of "Internet + hospital-to-home (H2H)" nutritional care model using the improved wavelet transform algorithm based on computed tomography (CT) images in the nutritional care management...

Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population.

International journal of environmental research and public health
(1) Background: The purpose of this study was to evaluate the efficacy in terms of sensitivity, specificity, and accuracy of the quantusSKIN system, a new clinical tool based on deep learning, to distinguish between benign skin lesions and melanoma i...

Workflow Integration of Research AI Tools into a Hospital Radiology Rapid Prototyping Environment.

Journal of digital imaging
The field of artificial intelligence (AI) in medical imaging is undergoing explosive growth, and Radiology is a prime target for innovation. The American College of Radiology Data Science Institute has identified more than 240 specific use cases wher...

Evaluating the safety and patient impacts of an artificial intelligence command centre in acute hospital care: a mixed-methods protocol.

BMJ open
INTRODUCTION: This paper presents a mixed-methods study protocol that will be used to evaluate a recent implementation of a real-time, centralised hospital command centre in the UK. The command centre represents a complex intervention within a comple...

Deep learning models for triaging hospital head MRI examinations.

Medical image analysis
The growing demand for head magnetic resonance imaging (MRI) examinations, along with a global shortage of radiologists, has led to an increase in the time taken to report head MRI scans in recent years. For many neurological conditions, this delay c...

Safety of robot-assisted radical prostatectomy in an Italian spoke hospital: Long-term oncologic and functional outcomes with median 11.3 years follow-up.

Urologia
INTRODUCTION: Robot-assisted radical prostatectomy (RARP) long-term oncologic outcomes were published in few studies. This paper provides a complete overview of RARP long-term oncologic and functional results produced in an Italian spoke hospital.