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Automatic analysis of high, medium, and low activities of broilers with heat stress operations via image processing and machine learning.
Poultry science
Feb 27, 2025
Heat stress is a major welfare problem in the poultry industry, altering broilers' activity levels. Advancements in image processing and machine learning provide opportunities to automatically quantify and analyze broiler activity. This study aimed t...
Long-Term Predictive Modelling of the Craniofacial Complex Using Machine Learning on 2D Cephalometric Radiographs.
International dental journal
Jan 5, 2025
OBJECTIVE: This study aimed to predict long-term growth-related changes in skeletal and dental relationships within the craniofacial complex using machine learning (ML) models.
Prediction of intra-abdominal injury using natural language processing of electronic medical record data.
Surgery
Jul 6, 2024
BACKGROUND: This study aimed to use natural language processing to predict the presence of intra-abdominal injury using unstructured data from electronic medical records.
Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.
Frontiers in endocrinology
Mar 28, 2024
PURPOSE: To develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs).
Deep learning algorithm (YOLOv7) for automated renal mass detection on contrast-enhanced MRI: a 2D and 2.5D evaluation of results.
Abdominal radiology (New York)
Feb 17, 2024
INTRODUCTION: Accurate diagnosis and treatment of kidney tumors greatly benefit from automated solutions for detection and classification on MRI. In this study, we explore the application of a deep learning algorithm, YOLOv7, for detecting kidney tum...
A Unified Multi-Class Feature Selection Framework for Microarray Data.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 25, 2023
In feature selection research, simultaneous multi-class feature selection technologies are popular because they simultaneously select informative features for all classes. Recursive feature elimination (RFE) methods are state-of-the-art binary featur...
Deep neural network for video colonoscopy of ulcerative colitis: a cross-sectional study.
The lancet. Gastroenterology & hepatology
Nov 29, 2021
BACKGROUND: A combination of endoscopic and histological evaluation is important in the management of patients with ulcerative colitis. We aimed to adapt our previous deep neural network system (deep neural ulcerative colitis [DNUC]) to full video co...
Deep learning with robustness to missing data: A novel approach to the detection of COVID-19.
PloS one
Jul 30, 2021
In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN (Denoising Fully Connected Network). Since medical facilities around the world differ enormously in what laborat...
Untangling the Animacy Organization of Occipitotemporal Cortex.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jul 6, 2021
Some of the most impressive functional specializations in the human brain are found in the occipitotemporal cortex (OTC), where several areas exhibit selectivity for a small number of visual categories, such as faces and bodies, and spatially cluster...
Machine Learning for Predicting the 3-Year Risk of Incident Diabetes in Chinese Adults.
Frontiers in public health
Jun 29, 2021
We aimed to establish and validate a risk assessment system that combines demographic and clinical variables to predict the 3-year risk of incident diabetes in Chinese adults. A 3-year cohort study was performed on 15,928 Chinese adults without dia...
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