AIMC Topic: Phenotype

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Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction.

Molecular plant Sep 7, 2022
The first paradigm of plant breeding involves direct selection-based phenotypic observation, followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental design and, more recently, by inco...
Plant Breeding Selection, Genetic Genome Phenotype Big Data Genomics Genotype Artificial Intelligence
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Weakly Semi-supervised phenotyping using Electronic Health records.

Journal of biomedical informatics Sep 5, 2022
OBJECTIVE: Electronic Health Record (EHR) based phenotyping is a crucial yet challenging problem in the biomedical field. Though clinicians typically determine patient-level diagnoses via manual chart review, the sheer volume and heterogeneity of EHR...
Algorithms Logistic Models Supervised Machine Learning Phenotype Electronic Health Records
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LeMeDISCO is a computational method for large-scale prediction & molecular interpretation of disease comorbidity.

Communications biology Aug 25, 2022
To understand the origin of disease comorbidity and to identify the essential proteins and pathways underlying comorbid diseases, we developed LeMeDISCO (Large-Scale Molecular Interpretation of Disease Comorbidity), an algorithm that predicts disease...
Artificial Intelligence Algorithms Phenotype Comorbidity Proteins
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OARD: Open annotations for rare diseases and their phenotypes based on real-world data.

American journal of human genetics Aug 22, 2022
Diagnosis for rare genetic diseases often relies on phenotype-driven methods, which hinge on the accuracy and completeness of the rare disease phenotypes in the underlying annotation knowledgebase. Existing knowledgebases are often manually curated w...
Electronic Health Records Natural Language Processing Rare Diseases Humans Phenotype
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PheValuator 2.0: Methodological improvements for the PheValuator approach to semi-automated phenotype algorithm evaluation.

Journal of biomedical informatics Aug 19, 2022
PURPOSE: Phenotype algorithms are central to performing analyses using observational data. These algorithms translate the clinical idea of a health condition into an executable set of rules allowing for queries of data elements from a database. PheVa...
Databases, Factual Reproducibility of Results Algorithms Phenotype Machine Learning
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Prediction and evaluation of combination pharmacotherapy using natural language processing, machine learning and patient electronic health records.

Journal of biomedical informatics Aug 17, 2022
Combination pharmacotherapy targets key disease pathways in a synergistic or additive manner and has high potential in treating complex diseases. Computational methods have been developed to identifying combination pharmacotherapy by analyzing large ...
Natural Language Processing Digoxin Hypertension Drug Combinations Hydrochlorothiazide Humans Machine Learning Phenotype Electronic Health Records
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Deep learning prediction of chemical-induced dose-dependent and context-specific multiplex phenotype responses and its application to personalized alzheimer's disease drug repurposing.

PLoS computational biology Aug 11, 2022
Predictive modeling of drug-induced gene expressions is a powerful tool for phenotype-based compound screening and drug repurposing. State-of-the-art machine learning methods use a small number of fixed cell lines as a surrogate for predicting actual...
Algorithms Phenotype Humans Alzheimer Disease Deep Learning Drug Repositioning
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High-throughput image-based plant stand count estimation using convolutional neural networks.

PloS one Jul 28, 2022
The landscape of farming and plant breeding is rapidly transforming due to the complex requirements of our world. The explosion of collectible data has started a revolution in agriculture to the point where innovation must occur. To a commercial orga...
Zea mays Algorithms Plant Breeding Neural Networks, Computer Phenotype
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Assessing the utility value of Hucul horses using classification models, based on artificial neural networks.

PloS one Jul 26, 2022
The aim of this study was to evaluate factors influencing the performance of Hucul horses and to develop a prediction model, based on artificial neural (AI) networks for predict horses' classification, relying on their performance value assessment du...
Animals Neural Networks, Computer Horses Phenotype
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Phenotypes of sickle cell intensive care admissions: an unsupervised machine learning approach in a single-center retrospective cohort.

Annals of hematology Jul 15, 2022
Sickle cell disease (SCD) is associated with multiple known complications and increased mortality. This study aims to further understand the profile of intensive care unit (ICU) admissions of SCD patients. In this single-center retrospective cohort (...
Anemia, Sickle Cell Unsupervised Machine Learning Critical Care Brazil Hospital Mortality Humans Female Phenotype Male Retrospective Studies Intensive Care Units
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