AIMC Topic: Biological Variation, Population

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PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework.

Nature genetics Aug 7, 2023
Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals...
Humans Artificial Intelligence Transcription Factors DNA-Binding Proteins Biological Variation, Population Matrix Attachment Region Binding Proteins Machine Learning Algorithms Phenotype
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Evidence for distinct neuro-metabolic phenotypes in humans.

NeuroImage Jan 13, 2022
Advances in magnetic resonance imaging have shown how individual differences in the structure and function of the human brain relate to health and cognition. The relationship between individual differences and the levels of neuro-metabolites, however...
Humans Magnetic Resonance Spectroscopy Biological Variation, Population Phenotype Female Support Vector Machine Adult Magnetic Resonance Imaging Male Gyrus Cinguli
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Deep learning enables genetic analysis of the human thoracic aorta.

Nature genetics Nov 26, 2021
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance i...
Aged Adult Male Middle Aged Humans Female Aortic Aneurysm Biological Variation, Population Image Processing, Computer-Assisted Transcriptome Magnetic Resonance Imaging Deep Learning Aorta, Thoracic Genome-Wide Association Study Quantitative Trait Loci
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Polycystic ovary syndrome: clinical and laboratory variables related to new phenotypes using machine-learning models.

Journal of endocrinological investigation Sep 15, 2021
PURPOSE: Polycystic Ovary Syndrome (PCOS) is the most frequent endocrinopathy in women of reproductive age. Machine learning (ML) is the area of artificial intelligence with a focus on predictive computing algorithms. We aimed to define the most rele...
Metabolic Networks and Pathways Polycystic Ovary Syndrome Preventive Health Services Biological Variation, Population Adult Insulin Resistance Body Mass Index Disease Hotspot Humans Artificial Intelligence Machine Learning Algorithms Precision Medicine Female
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Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning.

The Lancet. Digital health Jul 29, 2021
BACKGROUND: Parkinson's disease is heterogeneous in symptom presentation and progression. Increased understanding of both aspects can enable better patient management and improve clinical trial design. Previous approaches to modelling Parkinson's dis...
Biological Variation, Population Parkinson Disease Models, Statistical Biological Variation, Individual Dopamine Agents Middle Aged Humans Disease Progression Machine Learning Longitudinal Studies Female Aged Male
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Why do humans have unique auditory event-related fields? Evidence from computational modeling and MEG experiments.

Psychophysiology Jan 21, 2021
Auditory event-related fields (ERFs) measured with magnetoencephalography (MEG) are useful for studying the neuronal underpinnings of auditory cognition in human cortex. They have a highly subject-specific morphology, albeit certain characteristic de...
Magnetoencephalography Neural Networks, Computer Biological Variation, Population Humans Computer Simulation Auditory Cortex Evoked Potentials, Auditory
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A novel approach for personalized response model: deep learning with individual dropout feature ranking.

Journal of pharmacokinetics and pharmacodynamics Oct 26, 2020
Deep learning is the fastest growing field in artificial intelligence and has led to many transformative innovations in various domains. However, lack of interpretability sometimes hinders its application in hypothesis-driven domains such as biology ...
Humans Computer Simulation Precision Medicine Deep Learning Treatment Outcome Models, Biological Datasets as Topic Drug Therapy Biological Variation, Population
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A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.

Osteoarthritis and cartilage Apr 16, 2019
OBJECTIVE: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progressi...
Machine Learning Menisci, Tibial Databases, Factual Congresses as Topic Osteoarthritis, Knee Biomarkers Collagen Type II National Institutes of Health (U.S.) Female Disease Progression Cartilage, Articular Aged Biological Variation, Population Humans Severity of Illness Index Male United States Middle Aged Pain Measurement
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Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses.

Scientific reports Nov 2, 2018
Neurophysiological features like event-related potentials (ERPs) have long been used to identify different cognitive sub-processes that may contribute to task performance. It has however remained unclear whether "classical" ERPs are truly the best re...
Behavior Observation Techniques Electroencephalography Biological Variation, Population Evoked Potentials Reaction Time Humans Young Adult Inhibition, Psychological Healthy Volunteers Machine Learning Adult Neurophysiology Female Male Motor Cortex Models, Neurological
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