AIMC Topic: Machine Learning

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Predicting community acquired bloodstream infection in infants using full blood count parameters and C-reactive protein; a machine learning study.

European journal of pediatrics
Early recognition of bloodstream infection (BSI) in infants can be difficult, as symptoms may be non-specific, and culture can take up to 48 h. As a result, many infants receive unneeded antibiotic treatment while awaiting the culture results. In thi...

Advances in Extracellular Vesicle Research Over the Past Decade: Source and Isolation Method are Connected with Cargo and Function.

Advanced healthcare materials
The evolution of extracellular vesicle (EV) research has introduced nanotechnology into biomedical cell communication science while recognizing what is formerly considered cell "dust" as constituting an entirely new universe of cell signaling particl...

Using machine learning to identify key subject categories predicting the pre-clerkship and clerkship performance: 8-year cohort study.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Medical students need to build a solid foundation of knowledge to become physicians. Clerkship is often considered the first transition point, and clerkship performance is essential for their development. We hope to identify subjects that...

Utilising intraoperative respiratory dynamic features for developing and validating an explainable machine learning model for postoperative pulmonary complications.

British journal of anaesthesia
BACKGROUND: Timely detection of modifiable risk factors for postoperative pulmonary complications (PPCs) could inform ventilation strategies that attenuate lung injury. We sought to develop, validate, and internally test machine learning models that ...

Looking Beyond Mortality Prediction: Primary Care Physician Views of Patients' Palliative Care Needs Predicted by a Machine Learning Tool.

Applied clinical informatics
OBJECTIVES:  To assess primary care physicians' (PCPs) perception of the need for serious illness conversations (SIC) or other palliative care interventions in patients flagged by a machine learning tool for high 1-year mortality risk.

Prediction of jumbo drill penetration rate in underground mines using various machine learning approaches and traditional models.

Scientific reports
Estimating penetration rates of Jumbo drills is crucial for optimizing underground mining drilling processes, aiming to reduce costs and time. This study investigates various regression and machine learning methods, including Multilayer Perceptron (M...

Confirming the statistically significant superiority of tree-based machine learning algorithms over their counterparts for tabular data.

PloS one
Many individual studies in the literature observed the superiority of tree-based machine learning (ML) algorithms. However, the current body of literature lacks statistical validation of this superiority. This study addresses this gap by employing fi...

Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) AI Task Force along with experts in endoscopy, technology space, regulatory authorities, and other medical subspecialties initiated a consensus process that analyzed the ...

Machine-learning-based plasma metabolomic profiles for predicting long-term complications of cirrhosis.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: The complications of liver cirrhosis occur after long asymptomatic stages of progressive fibrosis and are generally diagnosed late. We aimed to develop a plasma metabolomic-based score tool to predict these events.

Vibrational spectroscopy coupled with machine learning sheds light on the cellular effects induced by rationally designed TLR4 agonists.

Talanta
In this work, we present the potential of Fourier transform infrared (FTIR) microspectroscopy to compare on whole cells, in an unbiased and untargeted way, the capacity of bacterial lipopolysaccharide (LPS) and two rationally designed molecules (FP20...