AIMC Topic: Machine Learning

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Gradient boosted trees with individual explanations: An alternative to logistic regression for viability prediction in the first trimester of pregnancy.

Computer methods and programs in biomedicine
BACKGROUND: Clinical models to predict first trimester viability are traditionally based on multivariable logistic regression (LR) which is not directly interpretable for non-statistical experts like physicians. Furthermore, LR requires complete data...

Three-Dimensional Visualization of the Podocyte Actin Network Using Integrated Membrane Extraction, Electron Microscopy, and Machine Learning.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Actin stress fibers are abundant in cultured cells, but little is known about them . In podocytes, much evidence suggests that mechanobiologic mechanisms underlie podocyte shape and adhesion in health and in injury, with structural change...

Machine Learning Models for Human Pharmacokinetic Parameters with In-House Validation.

Molecular pharmaceutics
Prior to clinical development, a comprehensive pharmacokinetic characterization of a novel drug is required to understand its exposure at the site of action and elimination. Accordingly, assays and animal pharmacokinetic studies are regularly employ...

A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

Nutrients
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...

Performance of Machine Learning-Based Multi-Model Voting Ensemble Methods for Network Threat Detection in Agriculture 4.0.

Sensors (Basel, Switzerland)
The upcoming agricultural revolution, known as Agriculture 4.0, integrates cutting-edge Information and Communication Technologies in existing operations. Various cyber threats related to the aforementioned integration have attracted increasing inter...

Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques.

BMC bioinformatics
BACKGROUND: Antimicrobial peptides are promising tools to fight against ever-growing antibiotic resistance. However, despite many advantages, their toxicity to mammalian cells is a critical obstacle in clinical application and needs to be addressed.

Employing phylogenetic tree shape statistics to resolve the underlying host population structure.

BMC bioinformatics
BACKGROUND: Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a populat...

Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 41...

Machine intelligence in non-invasive endocrine cancer diagnostics.

Nature reviews. Endocrinology
Artificial intelligence (AI) has illuminated a clear path towards an evolving health-care system replete with enhanced precision and computing capabilities. Medical imaging analysis can be strengthened by machine learning as the multidimensional data...

Survival prediction among heart patients using machine learning techniques.

Mathematical biosciences and engineering : MBE
Cardiovascular diseases are regarded as the most common reason for worldwide deaths. As per World Health Organization, nearly 17.9 million people die of heart-related diseases each year. The high shares of cardiovascular-related diseases in total wor...