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Advancement of post-market surveillance of medical devices leveraging artificial intelligence: Infusion pumps case study.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundAnalysis of data from incident registries such as MAUDE has identified the need to improve surveillance and maintenance strategies for infusion pumps to enhance patient and healthcare staff safety.ObjectiveThe ultimate goal is to enhance in...

Physics-Informed Neural Network for monitoring the sulfate ion adsorption process using particle filter.

Anais da Academia Brasileira de Ciencias
Fixed-bed columns are a well-established water purification technology. Several models have been constructed over the decades to scale up and predict the breakthrough curve of an adsorption column varying the flow rate, length, and initial concentrat...

A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa).

Environment international
Quantitative structure-activity relationships (QSARs) have been used to predict mixture toxicity. However, current research faces gaps in achieving accurate predictions of the mixture toxicity of azole fungicides. To address this gap, the application...

Leveraging machine learning in limited sampling strategies for efficient estimation of the area under the curve in pharmacokinetic analysis: a review.

European journal of clinical pharmacology
OBJECTIVE: Limited sampling strategies are widely employed in clinical practice to minimize the number of blood samples required for the accurate area under the curve calculations, as obtaining these samples can be costly and challenging. Traditional...

Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization.

Scientific reports
With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). Researc...

Development of a survey-based stacked ensemble predictive model for autonomy preferences in patients with periodontal disease.

Journal of dentistry
OBJECTIVES: This study aimed to develop a model to predict the autonomy preference (AP) and satisfaction after tooth extraction (STE) in patients with periodontal disease. Understanding of individual AP and STE is essential for improving patient sati...

Predictive risk models for COVID-19 patients using the multi-thresholding meta-algorithm.

Scientific reports
This study aims to develop a Machine Learning model to assess the risks faced by COVID-19 patients in a hospital setting, focusing specifically on predicting the complications leading to Intensive Care Unit (ICU) admission or mortality, which are min...

Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment.

Sensors (Basel, Switzerland)
Individual physiotherapy is crucial in treating patients with various pain and health issues, and significantly impacts abdominal surgical outcomes and further medical problems. Recent technological and artificial intelligent advancements have equipp...

Global greenhouse gas reduction forecasting via machine learning model in the scenario of energy transition.

Journal of environmental management
Global warming is becoming increasingly serious, with greenhouse gas (GHGs) emissions identified as a principal contributor. In response to the climate crisis, many countries are actively transitioning to renewable energy. Therefore, it is crucial to...

Artificial intelligence modeling of biomarker-based physiological age: Impact on phase 1 drug-metabolizing enzyme phenotypes.

CPT: pharmacometrics & systems pharmacology
Age and aging are important predictors of health status, disease progression, drug kinetics, and effects. The purpose was to develop ensemble learning-based physiological age (PA) models for evaluating drug metabolism. National Health and Nutrition E...