AIMC Topic: Machine Learning

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Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology.

JMIR mHealth and uHealth
BACKGROUND: There has been a recent increased interest in monitoring health using wearable sensor technologies; however, few have focused on breathing. The ability to monitor breathing metrics may have indications both for general health as well as r...

Machine learning approach to predict postoperative opioid requirements in ambulatory surgery patients.

PloS one
Opioids play a critical role in acute postoperative pain management. Our objective was to develop machine learning models to predict postoperative opioid requirements in patients undergoing ambulatory surgery. To develop the models, we used a periope...

Integral reinforcement learning based event-triggered control with input saturation.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel integral reinforcement learning (IRL)-based event-triggered adaptive dynamic programming scheme is developed for input-saturated continuous-time nonlinear systems. By using the IRL technique, the learning system does not requir...

Human Occupancy Detection via Passive Cognitive Radio.

Sensors (Basel, Switzerland)
Human occupancy detection (HOD) in an enclosed space, such as indoors or inside of a vehicle, via passive cognitive radio (CR) is a new and challenging research area. Part of the difficulty arises from the fact that a human subject cannot easily be d...

Predicting Crash Injury Severity with Machine Learning Algorithm Synergized with Clustering Technique: A Promising Protocol.

International journal of environmental research and public health
Predicting crash injury severity is a crucial constituent of reducing the consequences of traffic crashes. This study developed machine learning (ML) models to predict crash injury severity using 15 crash-related parameters. Separate ML models for ea...

Milk Source Identification and Milk Quality Estimation Using an Electronic Nose and Machine Learning Techniques.

Sensors (Basel, Switzerland)
In this study, an electronic nose (E-nose) consisting of seven metal oxide semiconductor sensors is developed to identify milk sources (dairy farms) and to estimate the content of milk fat and protein which are the indicators of milk quality. The dev...

The Role of Artificial Intelligence in Echocardiography.

Current cardiology reports
PURPOSE OF REVIEW: Echocardiography is an indispensable tool in diagnostic cardiology and is fundamental to clinical care. Significant advances in cardiovascular imaging technology paralleled by rapid growth in electronic medical records, miniaturize...

Modeling motivation for alcohol in humans using traditional and machine learning approaches.

Addiction biology
Given the significant cost of alcohol use disorder (AUD), identifying risk factors for alcohol seeking represents a research priority. Prominent addiction theories emphasize the role of motivation in the alcohol seeking process, which has largely bee...