AIMC Topic: Phenotype

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Genomic selection: Essence, applications, and prospects.

The plant genome Jun 1, 2025
Genomic selection (GS) emerged as a key part of the solution to ensure the food supply for the growing human population thanks to advances in genotyping and other enabling technologies and improved understanding of the genotype-phenotype relationship...
Plant Breeding Phenotype Genomics Genotype Crops, Agricultural Selection, Genetic Genome, Plant
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Zero-shot learning for clinical phenotyping: Comparing LLMs and rule-based methods.

Computers in biology and medicine Jun 1, 2025
BACKGROUND: Phenotyping, the process of systematically identifying and classifying conditions within clinical data, is a crucial first step in any data science work involving Electronic Health Records (EHRs). Traditional approaches require extensive ...
Humans Phenotype Machine Learning Electronic Health Records Natural Language Processing
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Deep learning and genomic best linear unbiased prediction integration: An approach to identify potential nonlinear genetic relationships between traits.

Journal of dairy science Jun 1, 2025
Genomic prediction (GP) aims to predict the breeding values of multiple complex traits, usually assumed to be multivariate normally distributed by the largely used statistical methods, thus imposing linear genetic relationships between traits. Althou...
Cattle Genomics Models, Genetic Milk Breeding Female Animals Deep Learning Phenotype
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Automated Deep Learning Phenotyping of Tricuspid Regurgitation in Echocardiography.

JAMA cardiology Jun 1, 2025
IMPORTANCE: Accurate assessment of tricuspid regurgitation (TR) is necessary for identification and risk stratification.
Female Aged Male Humans Phenotype ROC Curve Tricuspid Valve Insufficiency Middle Aged Echocardiography, Doppler, Color Severity of Illness Index Deep Learning
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Smartphone digital phenotyping in mental health disorders: A review of raw sensors utilized, machine learning processing pipelines, and derived behavioral features.

Psychiatry research Jun 1, 2025
With increased access to digital technology, there has been a surge in the use of and interest in digital phenotyping as a tool to calculate various features from raw smart device data. However, the increased usage of digital phenotyping has created ...
Machine Learning Phenotype Mental Disorders Smartphone Humans
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Digenic variant interpretation with hypothesis-driven explainable AI.

NAR genomics and bioinformatics Jun 1, 2025
The digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately interpreting and prioritizing digenic combinations of variants based on the proband's phenotypes and f...
Rare Diseases Humans Phenotype Artificial Intelligence Computational Biology Genetic Variation Machine Learning
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Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2025
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...
Male Dementia Diabetes Mellitus, Type 2 Phenotype Electronic Health Records Clinical Coding Hearing Loss, Sensorineural Prostatic Neoplasms Knowledge Bases Vocabulary, Controlled Humans
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Semi-Supervised PARAFAC2 Decomposition for Computational Phenotyping Using Electronic Health Records.

IEEE journal of biomedical and health informatics Jun 1, 2025
Computational phenotyping uses data mining methods to extract clusters of clinical descriptors, known as phenotypes, from electronic health records (EHR). Tensor factorization methods are very effective in extracting meaningful patterns and have beco...
Humans Electronic Health Records Supervised Machine Learning Data Mining Algorithms Phenotype
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Stroke prediction in elderly patients with atrial fibrillation using machine learning combined clinical and left atrial appendage imaging phenotypic features.

BMC cardiovascular disorders May 24, 2025
BACKGROUND: Atrial fibrillation (AF) is one of the primary etiologies for ischemic stroke, and it is of paramount importance to delineate the risk phenotypes among elderly AF patients and to investigate more efficacious models for predicting stroke r...
Atrial Appendage Decision Support Techniques Phenotype Prospective Studies Prognosis Female Risk Factors Humans Age Factors Risk Assessment Stroke Machine Learning Predictive Value of Tests Incidence Atrial Fibrillation Aged Ischemic Stroke Support Vector Machine Computed Tomography Angiography Aged, 80 and over Male
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Machine learning-based label-free macrophage phenotyping in immune-material interactions.

Journal of materials chemistry. B May 21, 2025
The rapid advancement of implantable biomedical materials necessitates a comprehensive understanding of macrophage interactions to optimize implant immunocompatibility. Macrophages, key immune regulators, exhibit phenotypic plasticity by polarizing i...
Collagen THP-1 Cells Biocompatible Materials Macrophages Humans Cytokines Machine Learning Phenotype
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