AIMC Topic: Linear Models

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Improving Operating Room Efficiency: Machine Learning Approach to Predict Case-Time Duration.

Journal of the American College of Surgeons
BACKGROUND: Accurate estimation of operative case-time duration is critical for optimizing operating room use. Current estimates are inaccurate and earlier models include data not available at the time of scheduling. Our objective was to develop stat...

Demographic, psychological, behavioral, and cognitive correlates of BMI in youth: Findings from the Adolescent Brain Cognitive Development (ABCD) study.

Psychological medicine
BACKGROUND: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to asses...

A robust machine learning enabled decomposition of shear ground reaction forces during the double contact phase of walking.

Gait & posture
BACKGROUND: Dynamic analyses of walking rely on the 3D ground reaction forces (GRF) under each foot, while only the resultant force of both limbs may be recorded on a single-belt instrumented treadmill or when both feet touch the same force platform.

Models of the effect of teleoperation transmission delay on robot movement time.

Ergonomics
Recent research of [Scholcover and Gillan ( 2018 )] has shown experimentally that system transmission delay has a linear effect on the time taken to perform a complex tracking task with a simple teleoperated robot. This note shows that, for the case ...

StomataCounter: a neural network for automatic stomata identification and counting.

The New phytologist
Stomata regulate important physiological processes in plants and are often phenotyped by researchers in diverse fields of plant biology. Currently, there are no user-friendly, fully automated methods to perform the task of identifying and counting st...

Using machine learning to understand the temporal morphology of the PM annual cycle in East Asia.

Environmental monitoring and assessment
PM air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have been established over the last decade to monitor real-time PM concentration. However, even thi...

Artificial neural network models to predict nodal status in clinically node-negative breast cancer.

BMC cancer
BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard staging procedure for nodal status in breast cancer, but lacks therapeutic benefit for patients with benign sentinel nodes. For patients with positive sentinel nodes, individualized surgical s...

A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide.

Environment international
Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary linear regression. However, different algorithms hav...

Combination of LEDs and cognitive modeling to quantify sheep cheese whey in watercourses.

Talanta
The concentration of sheep cheese whey (CW) in water obtained from two Spanish reservoirs, two Spanish rivers, and distilled water has been estimated by combining spectroscopic measurements, obtained with light-emitting diodes (LEDs), and linear or n...

A neural network-evolutionary computational framework for remaining useful life estimation of mechanical systems.

Neural networks : the official journal of the International Neural Network Society
This paper presents a framework for estimating the remaining useful life (RUL) of mechanical systems. The framework consists of a multi-layer perceptron and an evolutionary algorithm for optimizing the data-related parameters. The framework makes use...