AIMC Topic: Phenotype

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Unsupervised machine learning to identify subphenotypes among cardiac intensive care unit patients with heart failure.

ESC heart failure
AIMS: Hospitalized patients with heart failure (HF) are a heterogeneous population, with multiple phenotypes proposed. Prior studies have not examined the biological phenotypes of critically ill patients with HF admitted to the contemporary cardiac i...

MalariaFlow: A comprehensive deep learning platform for multistage phenotypic antimalarial drug discovery.

European journal of medicinal chemistry
Malaria remains a significant global health challenge due to the growing drug resistance of Plasmodium parasites and the failure to block transmission within human host. While machine learning (ML) and deep learning (DL) methods have shown promise in...

AI-based derivation of atrial fibrillation phenotypes in the general and critical care populations.

EBioMedicine
BACKGROUND: Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to a higher risk of mortality and morbidity. To predict AF and AF-related complications, clinical risk scores are commonly employed, but their predictive...

Machine Learning-Assisted Near-Infrared Spectral Fingerprinting for Macrophage Phenotyping.

ACS nano
Spectral fingerprinting has emerged as a powerful tool that is adept at identifying chemical compounds and deciphering complex interactions within cells and engineered nanomaterials. Using near-infrared (NIR) fluorescence spectral fingerprinting coup...

Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis.

JACC. Cardiovascular imaging
BACKGROUND: Adverse outcomes from moderate aortic stenosis (AS) may be caused by progression to severe AS or by the effects of comorbidities. In the absence of randomized trial evidence favoring aortic valve replacement (AVR) in patients with moderat...

Unraveling phenotypic heterogeneity in stanford type B aortic dissection patients through machine learning clustering analysis of cardiovascular CT imaging.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese
OBJECTIVE: Aortic dissection remains a life-threatening condition necessitating accurate diagnosis and timely intervention. This study aimed to investigate phenotypic heterogeneity in patients with Stanford type B aortic dissection (TBAD) through mac...

Artificial intelligence in plant breeding.

Trends in genetics : TIG
Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scien...

Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.

Neurocritical care
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.

New insights on hidradenitis suppurativa phenotypes and treatment response: An exploratory automated analysis of the SUNSHINE and SUNRISE trials.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Defining hidradenitis suppurativa (HS) subtypes was previously limited by small sample sizes and poor interrater reliability; no study has investigated subtype treatment responses. The objective of this analysis was to characterize HS clu...

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

Genomics
This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neu...