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Hospitals

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Developing EMR-based algorithms to Identify hospital adverse events for health system performance evaluation and improvement: Study protocol.

PloS one
BACKGROUND: Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. El...

De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models.

Journal of biomedical informatics
Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value to medical researchers. However, this information is mixed with Personally Identifiable Information (PII) that presents risks to patient and clinician ...

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network.

Respiratory research
BACKGROUND: Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both individual risk str...

Cost analysis of implementing a vial-sharing strategy for chemotherapy drugs using intelligent dispensing robots in a tertiary Chinese hospital in Sichuan.

Frontiers in public health
INTRODUCTION: Chemotherapy drug wasting is a huge problem in oncology that not only results in excessive expenses on chemotherapy drugs but also increases the cost of disposing of chemotherapy waste and the risk of occupational exposure in the enviro...

Analysis of the Exploration of Security and Privacy for Healthcare Management Using Artificial Intelligence: Saudi Hospitals.

Computational intelligence and neuroscience
A large component of the Health Information Systems now comprises numerous independent apps created in the past that need to be merged to provide a more uniform service. In addition to affecting the Intelligent Health Board Functionality and dependab...

Pre-hospital prediction of adverse outcomes in patients with suspected COVID-19: Development, application and comparison of machine learning and deep learning methods.

Computers in biology and medicine
BACKGROUND: COVID-19 infected millions of people and increased mortality worldwide. Patients with suspected COVID-19 utilised emergency medical services (EMS) and attended emergency departments, resulting in increased pressures and waiting times. Rap...

Occupational health and safety risk assessment using a fuzzy multi-criteria approach in a hospital in Chennai, India.

International journal of occupational safety and ergonomics : JOSE
Hospitals provide direct and indirect employment benefits to medical professionals. Accidents in hospitals often lead to disastrous consequences such as fatalities, property damage and economic losses. It is, therefore, imperative to have an occupat...

Similar hospital profits with robotic-assisted paraesophageal hiatal hernia repair, despite higher or supply costs.

Surgical endoscopy
INTRODUCTION: Robotic-assisted laparoscopic surgery has emerged as an alternative to traditional laparoscopy and may offer some clinical benefits when performing complex hiatal hernia repairs. Many institutions may choose to not invest in robotic sur...

Hospital Intelligent Power Operation and Maintenance Information Evaluation with the Long and Short Memory Neural Network.

BioMed research international
The invention describes a deep learning-based technique for monitoring power grid information operation and maintenance. Based on the time series data information in the power grid information operation and maintenance monitoring system, this method ...