AIMC Topic: Phenotype
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Identifying predictors of the tooth loss phenotype in a large periodontitis patient cohort using a machine learning approach.
Journal of dentistry
Mar 2, 2024
OBJECTIVES: This study aimed to identify predictors associated with the tooth loss phenotype in a large periodontitis patient cohort in the university setting.
GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM.
BMC bioinformatics
Feb 27, 2024
BACKGROUND: Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the info...
Machine learning methods for genomic prediction of cow behavioral traits measured by automatic milking systems in North American Holstein cattle.
Journal of dairy science
Feb 22, 2024
Identifying genome-enabled methods that provide more accurate genomic prediction is crucial when evaluating complex traits such as dairy cow behavior. In this study, we aimed to compare the predictive performance of traditional genomic prediction met...
Machine learning clustering of adult spinal deformity patients identifies four prognostic phenotypes: a multicenter prospective cohort analysis with single surgeon external validation.
The spine journal : official journal of the North American Spine Society
Feb 15, 2024
BACKGROUND CONTEXT: Among adult spinal deformity (ASD) patients, heterogeneity in patient pathology, surgical expectations, baseline impairments, and frailty complicates comparisons in clinical outcomes and research. This study aims to qualitatively ...
Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.
Journal for immunotherapy of cancer
Feb 14, 2024
BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it i...
The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks.
Scientific reports
Feb 10, 2024
The emergence of publicly accessible artificial intelligence (AI) large language models such as ChatGPT has given rise to global conversations on the implications of AI capabilities. Emergent research on AI has challenged the assumption that creative...
Characterizing advanced heart failure risk and hemodynamic phenotypes using interpretable machine learning.
American heart journal
Feb 7, 2024
BACKGROUND: Although previous risk models exist for advanced heart failure with reduced ejection fraction (HFrEF), few integrate invasive hemodynamics or support missing data. This study developed and validated a heart failure (HF) hemodynamic risk a...
AI-based diagnosis and phenotype - Genotype correlations in syndromic craniosynostoses.
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Feb 5, 2024
Apert (AS), Crouzon (CS), Muenke (MS), Pfeiffer (PS), and Saethre Chotzen (SCS) are among the most frequently diagnosed syndromic craniosynostoses. The aims of this study were (1) to train an innovative model using artificial intelligence (AI)-based ...
A neural network model for the evolution of learning in changing environments.
PLoS computational biology
Jan 30, 2024
Learning from past experience is an important adaptation and theoretical models may help to understand its evolution. Many of the existing models study simple phenotypes and do not consider the mechanisms underlying learning while the more complex ne...
Next generation phenotyping for diagnosis and phenotype-genotype correlations in Kabuki syndrome.
Scientific reports
Jan 28, 2024
The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photog...
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