AIMC Topic: Phenotype

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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
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
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
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
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
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
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
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...

Plant microphenotype: from innovative imaging to computational analysis.

Plant biotechnology journal
The microphenotype plays a key role in bridging the gap between the genotype and the complex macro phenotype. In this article, we review the advances in data acquisition and the intelligent analysis of plant microphenotyping and present applications ...

ScabyNet, a user-friendly application for detecting common scab in potato tubers using deep learning and morphological traits.

Scientific reports
Common scab (CS) is a major bacterial disease causing lesions on potato tubers, degrading their appearance and reducing their market value. To accurately grade scab-infected potato tubers, this study introduces "ScabyNet", an image processing approac...

Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes.

Nature methods
It is poorly understood how different cells in a tissue organize themselves to support tissue functions. We describe the CytoCommunity algorithm for the identification of tissue cellular neighborhoods (TCNs) based on cell phenotypes and their spatial...