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Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis.
Scientific reports
Mar 5, 2025
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...
Cold storage surpasses the impact of biological age and donor characteristics on red blood cell morphology classified by deep machine learning.
Scientific reports
Mar 5, 2025
Assessment of the morphology of red blood cells (RBCs) can improve clinical benefits following blood transfusion. Deep machine learning surpasses traditional microscopy-based classification methods, offering more accurate and consistent results while...
Separation of stroke from vestibular neuritis using the video head impulse test: machine learning models versus expert clinicians.
Journal of neurology
Mar 5, 2025
BACKGROUND: Acute vestibular syndrome usually represents either vestibular neuritis (VN), an innocuous viral illness, or posterior circulation stroke (PCS), a potentially life-threatening event. The video head impulse test (VHIT) is a quantitative me...
Epidemiology and risk factors of Clonorchis sinensis infection in the mountainous areas of Longsheng County, Guangxi: insights from automated machine learning.
Parasitology research
Mar 5, 2025
Clonorchis sinensis (C. sinensis) is mainly prevalent in Northeast and South China, with Guangxi being the most severely affected region. This study aimed to evaluate the prevalence and identify the risk factors of C. sinensis infection in Longsheng ...
Machine Learning-Based Prediction of Delirium and Risk Factor Identification in Intensive Care Unit Patients With Burns: Retrospective Observational Study.
JMIR formative research
Mar 5, 2025
BACKGROUND: The incidence of delirium in patients with burns receiving treatment in the intensive care unit (ICU) is high, reaching up to 77%, and has been associated with increased mortality rates. Therefore, early identification of patients at high...
Multi-task interaction learning for accurate segmentation and classification of breast tumors in ultrasound images.
Physics in medicine and biology
Mar 5, 2025
In breast diagnostic imaging, the morphological variability of breast tumors and the inherent ambiguity of ultrasound images pose significant challenges. Moreover, multi-task computer-aided diagnosis systems in breast imaging may overlook inherent re...
Use of natural language processing method to identify regional anesthesia from clinical notes.
Regional anesthesia and pain medicine
Mar 5, 2025
INTRODUCTION: Accurate data capture is integral for research and quality improvement efforts. Unfortunately, limited guidance for defining and documenting regional anesthesia has resulted in wide variation in documentation practices, even within indi...
Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non-Small Cell Lung Cancer.
JCO clinical cancer informatics
Mar 5, 2025
PURPOSE: To comprehensively analyze the association between preoperative maximum standardized uptake value (SUV) on 18F-fluorodeoxyglucose positron emission tomography-computed tomography and postoperative recurrence in resected non-small cell lung c...
AI-determined similarity increases likability and trustworthiness of human voices.
PloS one
Mar 5, 2025
Modern artificial intelligence (AI) technology is capable of generating human sounding voices that could be used to deceive recipients in various contexts (e.g., deep fakes). Given the increasing accessibility of this technology and its potential soc...
ABVS breast tumour segmentation via integrating CNN with dilated sampling self-attention and feature interaction Transformer.
Neural networks : the official journal of the International Neural Network Society
Mar 4, 2025
Given the rapid increase in breast cancer incidence, the Automated Breast Volume Scanner (ABVS) is developed to screen breast tumours efficiently and accurately. However, reviewing ABVS images is a challenging task owing to the significant variations...
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