AIMC Topic: Phenotype

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Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods.

Journal of animal science
The aim of this study was to compare the predictive performance of the Genomic Best Linear Unbiased Predictor (GBLUP) and machine learning methods (Random Forest, RF; Support Vector Machine, SVM; Artificial Neural Network, ANN) in simulated populatio...

Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.

GigaScience
BACKGROUND: Shape is a critical element of the visual appeal of strawberry fruit and is influenced by both genetic and non-genetic determinants. Current fruit phenotyping approaches for external characteristics in strawberry often rely on the human e...

Forecasting beef production and quality using large-scale integrated data from Brazil.

Journal of animal science
With agriculture rapidly becoming a data-driven field, it is imperative to extract useful information from large data collections to optimize the production systems. We compared the efficacy of regression (linear regression or generalized linear regr...

DeepPod: a convolutional neural network based quantification of fruit number in Arabidopsis.

GigaScience
BACKGROUND: High-throughput phenotyping based on non-destructive imaging has great potential in plant biology and breeding programs. However, efficient feature extraction and quantification from image data remains a bottleneck that needs to be addres...

Systematic Review of Digital Phenotyping and Machine Learning in Psychosis Spectrum Illnesses.

Harvard review of psychiatry
BACKGROUND: Digital phenotyping is the use of data from smartphones and wearables collected in situ for capturing a digital expression of human behaviors. Digital phenotyping techniques can be used to analyze both passively (e.g., sensor) and activel...

Technology-Based Objective Measures Detect Subclinical Axial Signs in Untreated, de novo Parkinson's Disease.

Journal of Parkinson's disease
BACKGROUND: Technology-based objective measures (TOMs) recently gained relevance to support clinicians in the assessment of motor function in Parkinson's disease (PD), although limited data are available in the early phases.

Identification of disease-associated loci using machine learning for genotype and network data integration.

Bioinformatics (Oxford, England)
MOTIVATION: Integration of different omics data could markedly help to identify biological signatures, understand the missing heritability of complex diseases and ultimately achieve personalized medicine. Standard regression models used in Genome-Wid...

A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography.

European heart journal
BACKGROUND: Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). Howeve...

Data-driven method to enhance craniofacial and oral phenotype vocabularies.

Journal of the American Dental Association (1939)
BACKGROUND: A significant amount of clinical information captured as free-text narratives could be better used for several applications, such as clinical decision support, ontology development, evidence-based practice, and research. The Human Phenoty...

High-throughput multimodal automated phenotyping (MAP) with application to PheWAS.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop ...