AIMC Topic: Machine Learning

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Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension.

The Journal of surgical research
BACKGROUND: Models that predict postoperative complications often ignore important intraoperative events and physiological changes. This study tested the hypothesis that accuracy, discrimination, and precision in predicting postoperative complication...

Deep learning networks for the recognition and quantitation of surface-enhanced Raman spectroscopy.

The Analyst
Surface-enhanced Raman spectroscopy (SERS) based on machine learning methods has been applied in material analysis, biological detection, food safety, and intelligent analysis. However, machine learning methods generally require extra preprocessing o...

Behavioral Activity Recognition Based on Gaze Ethograms.

International journal of neural systems
Noninvasive behavior observation techniques allow more natural human behavior assessment experiments with higher ecological validity. We propose the use of gaze ethograms in the context of user interaction with a computer display to characterize the ...

Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach.

International journal of environmental research and public health
Road traffic injury accounts for a substantial human and economic burden globally. Understanding risk factors contributing to fatal injuries is of paramount importance. In this study, we proposed a model that adopts a hybrid ensemble machine learning...

A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems.

mBio
Machine learning (ML) modeling of the human microbiome has the potential to identify microbial biomarkers and aid in the diagnosis of many diseases such as inflammatory bowel disease, diabetes, and colorectal cancer. Progress has been made toward dev...

The use of machine learning in rare diseases: a scoping review.

Orphanet journal of rare diseases
BACKGROUND: Emerging machine learning technologies are beginning to transform medicine and healthcare and could also improve the diagnosis and treatment of rare diseases. Currently, there are no systematic reviews that investigate, from a general per...

Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Diagnostic microbiology and infectious disease
Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective coho...

Operational framework and training standard requirements for AI-empowered robotic surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: For autonomous robot-delivered surgeries to ever become a feasible option, we recommend the combination of human-centered artificial intelligence (AI) and transparent machine learning (ML), with integrated Gross anatomy models. This can b...