Predictive health monitoring: Leveraging artificial intelligence for early detection of infectious diseases in nursing home residents through discontinuous vital signs analysis.

This research addresses the problem of detecting acute respiratory, urinary tract, and other infectious diseases in elderly nursing home residents using machine learning algorithms. The study analyzes data extracted from multiple vital signs and other contextual information for diagnostic purposes. The daily data collection process encounters sampling constraints due to weekends, holidays, shift changes, staff turnover, and equipment breakdowns, resulting in numerous nulls, repeated readings, outliers, and meaningless values.

Medical Prognosis of Infectious Diseases in Nursing Homes by Applying Machine Learning on Clinical Data Collected in Cloud Microservices.

Background: treating infectious diseases in elderly individuals is difficult; patient referral to emergency services often occurs, since the elderly tend to arrive at consultations with advanced, serious symptoms.

Aim: it was hypothesized that anticipating an infectious disease diagnosis by a few days could significantly improve a patient's well-being and reduce the burden on emergency health system services.

Methods: vital signs from residents were taken daily and transferred to a database in the cloud.

Predicting the Appearance of Hypotension During Hemodialysis Sessions Using Machine Learning Classifiers.

A patient suffering from advanced chronic renal disease undergoes several dialysis sessions on different dates. Several clinical parameters are monitored during the different hours of any of these sessions. These parameters, together with the information provided by other parameters of analytical nature, can be very useful to determine the probability that a patient may suffer from hypotension during the session, which should be specially watched since it represents a proven factor of possible mortality.

Physical Restraint Use With Elderly Patients: Perceptions of Nurses and Nursing Assistants in Spanish Acute Care Hospitals.

Background: Physical restraint is often used during the hospitalization of elderly people. However, this procedure is associated with adverse outcomes; therefore, it is necessary to be aware of the circumstances that promote restraint use, such as the perceptions of professionals who use it.

Objectives: The purpose of the research was to determine the situations in which nursing staff considered the use of physical restraint as most important and to evaluate the possible associations with the sociodemographic and professional variables.

Sequential preconcentration and on-membrane Raman determination of carboxylic single-walled carbon nanotubes in river water samples.

This article proposes a simple and sensitive approach for the preconcentration and determination of carboxylated single-walled carbon nanotubes (c-SWNTs) in environmental samples using membranes modified with multiwalled carbon nanotubes (MWNTs). The method is based on the preconcentration of c-SWNTs and their direct on-filter Raman spectroscopic analysis. The preconcentration of c-SWNTs is performed by microfiltrating the sample through a cellulose membrane modified with MWNTs fabricated from a surfactant dispersion of the same.