Linear Models

Driving Cognitive Alertness Detecting Using Evoked Multimodal Physiological Signals Based on Uncertain Self-Supervised Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 38848231

Multimodal physiological signals play a pivotal role in drivers' perception of work stress. However, the scarcity of labels and the multitude of modalities render the utilization of physiological signals for driving cognitive alertness detection chal...

Algorithms Attention Automobile Driving Cognition Electroencephalography Entropy Heart Rate Humans Linear Models Male Supervised Machine Learning Uncertainty

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A Bayesian convolutional neural network-based generalized linear model.

Biometrics 38888097

Convolutional neural networks (CNNs) provide flexible function approximations for a wide variety of applications when the input variables are in the form of images or spatial data. Although CNNs often outperform traditional statistical models in pred...

Algorithms Bayes Theorem Brain Neoplasms Humans Linear Models Magnetic Resonance Imaging Malaria Monte Carlo Method Neural Networks, Computer

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Age Estimation by Machine Learning and CT-Multiplanar Reformation of Cranial Sutures in Northern Chinese Han Adults.

Fa yi xue za zhi 38847026

OBJECTIVES: To establish age estimation models of northern Chinese Han adults using cranial suture images obtained by CT and multiplanar reformation (MPR), and to explore the applicability of cranial suture closure rule in age estimation of northern ...

Adult Age Determination by Skeleton Aged Aged, 80 and over Bayes Theorem China Cranial Sutures East Asian People Ethnicity Female Forensic Anthropology Humans Image Processing, Computer-Assisted Imaging, Three-Dimensional Linear Models Machine Learning Male Middle Aged Retrospective Studies Skull Tomography, X-Ray Computed

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Growth period determination and color coordinates visual analysis of tomato using hyperspectral imaging technology.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy 38833885

Growth period determination and color coordinates prediction are essential for comparing postharvest fruit quality. This paper proposes a tomato growth period judgment and color coordinates prediction model based on hyperspectral imaging technology. ...

Algorithms Color Discriminant Analysis Fruit Hyperspectral Imaging Least-Squares Analysis Linear Models Principal Component Analysis Solanum lycopersicum Support Vector Machine

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Predicting the governing factors for the release of colloidal phosphorus using machine learning.

Chemosphere 38944354

Predicting the parameters that influence colloidal phosphorus (CP) release from soils under different land uses is critical for managing the impact on water quality. Traditional modeling approaches, such as linear regression, may fail to represent th...

Colloids Environmental Monitoring Iron Linear Models Machine Learning Phosphorus Soil Soil Pollutants

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Chaotic neural network algorithm with competitive learning integrated with partial Least Square models for the prediction of the toxicity of fragrances in sanitizers and disinfectants.

The Science of the total environment 38844215

This study addresses the need for accurate structural data regarding the toxicity of fragrances in sanitizers and disinfectants. We compare the predictive and descriptive (model stability) potential of multiple linear regression (MLR) and partial lea...

Algorithms Disinfectants Least-Squares Analysis Linear Models Neural Networks, Computer Perfume

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Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling.

Scientific reports 38830957

Fungicide mixtures are an effective strategy in delaying the development of fungicide resistance. In this research, a fixed ratio ray design method was used to generate fifty binary mixtures of five fungicides with diverse modes of action. The intera...

Fungicides, Industrial Linear Models Machine Learning Neural Networks, Computer Quantitative Structure-Activity Relationship Support Vector Machine

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Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society 39096750

This paper deals with the lag projective synchronization (LPS) problem for a class of discrete-time fractional-order quaternion-valued neural networks(DTFO QVNNs) systems with time delays. Firstly, a DTFOQVNNs system with time delay is constructed. S...

Algorithms Computer Simulation Feedback Linear Models Neural Networks, Computer Nonlinear Dynamics Time Factors

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Prediction of retention data of phenolic compounds by quantitative structure retention relationship models under reverse-phase liquid chromatography.

Journal of chromatography. A 39025025

Quantitative Structure-Retention Relationship models were developed to identify phenolic compounds using a typical LC- system, with both UV and MS detection. A new chromatographic method was developed for the separation of fifty-two standard phenolic...

Algorithms Chromatography, High Pressure Liquid Chromatography, Reverse-Phase Flavonoids Least-Squares Analysis Linear Models Models, Chemical Neural Networks, Computer Phenols Quantitative Structure-Activity Relationship

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Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.

Journal of applied gerontology : the official journal of the Southern Gerontological Society 39105424

This study aimed to develop and validate prediction models for incident reversible cognitive frailty (RCF) based on social-ecological predictors. Older adults aged ≥60 years from China Health and Retirement Longitudinal Study (CHARLS) 2011-2013 surve...

Aged Aged, 80 and over Algorithms China Cognitive Dysfunction Female Frail Elderly Frailty Humans Linear Models Longitudinal Studies Machine Learning Male Middle Aged Prospective Studies Risk Assessment Risk Factors

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Explore the latest research on artificial intelligence and machine learning in medicine.

Driving Cognitive Alertness Detecting Using Evoked Multimodal Physiological Signals Based on Uncertain Self-Supervised Learning.

A Bayesian convolutional neural network-based generalized linear model.

Age Estimation by Machine Learning and CT-Multiplanar Reformation of Cranial Sutures in Northern Chinese Han Adults.

Growth period determination and color coordinates visual analysis of tomato using hyperspectral imaging technology.

Predicting the governing factors for the release of colloidal phosphorus using machine learning.

Chaotic neural network algorithm with competitive learning integrated with partial Least Square models for the prediction of the toxicity of fragrances in sanitizers and disinfectants.

Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling.

Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays.

Prediction of retention data of phenolic compounds by quantitative structure retention relationship models under reverse-phase liquid chromatography.

Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.

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