AIMC Topic: Machine Learning

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A review of the journey of field crop phenotyping: From trait stamp collections and fancy robots to phenomics-informed crop performance predictions.

Journal of plant physiology
Crop phenotyping encompasses methodologies for measuring plant growth, architecture, and composition with high precision across scales, from organs to canopies. Field-based phenotyping is pivotal in bridging genomic data with crop performance, offeri...

Multi-Target Drug Design in Alzheimer's Disease Treatment: Emerging Technologies, Advantages, Challenges, and Limitations.

Pharmacology research & perspectives
Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disorder, recognized as the most prevalent form of dementia. It is characterized by multiple pathological processes, including amyloid-beta accumulation, neurofibrillary tangl...

Examining 81 Predictors of Self-Esteem Using Machine Learning.

International journal of psychology : Journal international de psychologie
The purpose of this study was to identify and rank the most important predictors of self-esteem. Data were drawn from the Midlife in the United States (MIDUS) study, a nationally representative survey of American adults. A total of 81 potential predi...

Sex-estimation method for three-dimensional shapes of the skull and skull parts using machine learning.

Forensic science international
Sex estimation is an indispensable test for identifying skeletal remains in the field of forensic anthropology. We developed a novel sex-estimation method for skulls and several parts of the skull using machine learning. A total of 240 skull shapes w...

Analysis of the neural mechanisms of social anxiety based on EEG features and machine learning and construction of a diagnostic model.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Social anxiety is a common psychological problem, and its accurate diagnosis and investigation of underlying neurophysiological mechanisms are of significant importance. This study aims to explore the neuroelectrophysiological characteristics and dia...

Artificial intelligence, machine learning, and digitalization systems in the cell and gene therapy sector: a guidance document from the ISCT industry committees.

Cytotherapy
As artificial intelligence (AI), machine learning (ML) and other digital tools gain prominence across industries, their application in cell and gene therapy (CGT) has become a topic of increasing interest. Discussions at recent meetings of the Intern...

Performance analysis of machine learning algorithms for the prediction of disinfection byproducts formation during chlorination: Effect of background water characteristics.

Journal of environmental management
This study investigated the comparison of the nonlinear machine learning algorithms and linear regression models to predict the formation of trihalomethanes (THM4), haloacetic acids (HAA5 and HAA9), and haloacetonitriles (HAN4 and HAN6) under uniform...

Air quality monitoring and mitigation through time series forecasting and stochastic optimization.

Journal of environmental management
Poor air quality poses significant threats to public health and environmental sustainability. To mitigate such risks, accurate air quality prediction is essential to inform intervention policies that effectively reduce pollutant levels. While past re...

Analysis of disease severity and mortality prediction using machine learning during COVID-19.

Acta psychologica
This paper focuses on how machine learning (ML) algorithms and applications have been used to analyze disease severity and mortality prediction in COVID-19 research. In the past, simpler statistical and epidemiological methods were more commonly used...

Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure.

Computers in biology and medicine
Anorexia nervosa (AN), a severe eating disorder marked by extreme weight loss and malnutrition, leads to significant alterations in brain structure. This study used machine learning (ML) to estimate brain age from structural MRI scans and investigate...