AIMC Topic: Phenotype
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Plant microphenotype: from innovative imaging to computational analysis.
Plant biotechnology journal
Jan 13, 2024
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
Jan 13, 2024
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
Jan 8, 2024
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...
Prediction of six macrophage phenotypes and their IL-10 content based on single-cell morphology using artificial intelligence.
Frontiers in immunology
Jan 4, 2024
INTRODUCTION: The last decade has led to rapid developments and increased usage of computational tools at the single-cell level. However, our knowledge remains limited in how extracellular cues alter quantitative macrophage morphology and how such mo...
Using machine learning and partial dependence to evaluate robustness of best linear unbiased prediction (BLUP) for phenotypic values.
Journal of applied genetics
Jan 3, 2024
Best linear unbiased prediction (BLUP) is widely used in plant research to address experimental variation. For phenotypic values, BLUP accuracy is largely dependent on properly controlled experimental repetition and how variable components are outlin...
Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning.
Medical image analysis
Dec 28, 2023
We propose DiRL, a Diversity-inducing Representation Learning technique for histopathology imaging. Self-supervised learning (SSL) techniques, such as contrastive and non-contrastive approaches, have been shown to learn rich and effective representat...
Predictive value of preoperative Fried Frailty Phenotype assessment and serum biomarkers on the prognosis of elderly patients with femoral neck fracture under general anesthesia within 3 months after surgery.
Turkish journal of medical sciences
Dec 11, 2023
BACKGROUND/AIM: Femoral neck fracture (FNF) seriously impact the health of the elderly and affect their long-term quality of life of the patients. This study aimed to determine whether combining the preoperative Fried Frailty Phenotype (FFP) with ser...
Novel Preoperative Risk Stratification Using Digital Phenotyping Applying a Scalable Machine-Learning Approach.
Anesthesia and analgesia
Dec 5, 2023
BACKGROUND: Classification of perioperative risk is important for patient care, resource allocation, and guiding shared decision-making. Using discriminative features from the electronic health record (EHR), machine-learning algorithms can create dig...
Achalasia phenotypes and prediction of peroral endoscopic myotomy outcomes using machine learning.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Dec 1, 2023
OBJECTIVES: High-resolution manometry (HRM) and esophagography are used for achalasia diagnosis; however, achalasia phenotypes combining esophageal motility and morphology are unknown. Moreover, predicting treatment outcomes of peroral endoscopic myo...
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