AIMC Topic: Young Adult

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Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.

PloS one
BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts fo...

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids.

Clinical therapeutics
PURPOSE: Coronavirus disease-2019 (COVID-19) continues to be a global threat and remains a significant cause of hospitalizations. Recent clinical guidelines have supported the use of corticosteroids or remdesivir in the treatment of COVID-19. However...

Pharmacokinetics of Eltrombopag in Healthy Chinese Subjects and Effect of Sex and Genetic Polymorphism on its Pharmacokinetic and Pharmacodynamic Variability.

European journal of drug metabolism and pharmacokinetics
BACKGROUND AND OBJECTIVE: Eltrombopag is the first oral, small-molecule, non-peptide thrombopoietin receptor agonist for the treatment of idiopathic thrombocytopenic purpura. This study investigated the pharmacokinetics of eltrombopag in healthy Chin...

The Influence of Fluid Intake Behavior on Cognition and Mood among College Students in Baoding, China.

Annals of nutrition & metabolism
INTRODUCTION: Water is a critical nutrient, and it is important for the maintenance of the physiological function of the human body [1-3]. In addition to fluid amounts, f...

U-net model for brain extraction: Trained on humans for transfer to non-human primates.

NeuroImage
Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess such as image registration, tissue classification, etc. Most brain extraction tools have been designed...

Predicting postoperative opioid use with machine learning and insurance claims in opioid-naïve patients.

American journal of surgery
BACKGROUND: The clinical impact of postoperative opioid use requires accurate prediction strategies to identify at-risk patients. We utilize preoperative claims data to predict postoperative opioid refill and new persistent use in opioid-naïve patien...

Early identification of epilepsy surgery candidates: A multicenter, machine learning study.

Acta neurologica Scandinavica
OBJECTIVES: Epilepsy surgery is underutilized. Automating the identification of potential surgical candidates may facilitate earlier intervention. Our objective was to develop site-specific machine learning (ML) algorithms to identify candidates befo...

Understanding Attitudes to Change to Healthier Hydration Habits: The Case of High Sugar: Low Water Drinkers in Mexico.

Annals of nutrition & metabolism
Adults consuming sugar-sweetened beverages (SSBs) are at increased risk of becoming overweight/obese and developing lifestyle-related diseases. Furthermore, a low water intake is associated with increased health risks, such as CKD. These issues are e...

Machine learning associated with respiratory oscillometry: a computer-aided diagnosis system for the detection of respiratory abnormalities in systemic sclerosis.

Biomedical engineering online
INTRODUCTION: The use of machine learning (ML) methods would improve the diagnosis of respiratory changes in systemic sclerosis (SSc). This paper evaluates the performance of several ML algorithms associated with the respiratory oscillometry analysis...

Design of a hesitant movement gesture for mobile robots.

PloS one
In previous experiments, a back-off movement was introduced as a motion strategy of robots to facilitate the order of passage at bottlenecks in human-robot spatial interaction. In this article we take a closer look at the appropriate application of m...