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Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions.
Scientific reports
Dec 28, 2024
This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breas...
Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models.
Scientific reports
Dec 28, 2024
Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like permanent neurological damage or death. Early detection using deep learning (DL) and machine learning (ML) models can enhance patient outcomes and miti...
Early prediction of functional impairment at hospital discharge in patients with osteoporotic vertebral fracture: a machine learning approach.
Scientific reports
Dec 28, 2024
Although conservative treatment is commonly used for osteoporotic vertebral fracture (OVF), some patients experience functional disability following OVF. This study aimed to develop prediction models for new-onset functional impairment following admi...
Predicting host health status through an integrated machine learning framework: insights from healthy gut microbiome aging trajectory.
Scientific reports
Dec 28, 2024
The gut microbiome, recognized as a critical component in the development of chronic diseases and aging processes, constitutes a promising approach for predicting host health status. Previous research has underscored the potential of microbiome-based...
Predictive modelling of hospital-acquired infection in acute ischemic stroke using machine learning.
Scientific reports
Dec 28, 2024
Hospital-acquired infections (HAIs) are serious complication for patients with acute ischemic stroke (AIS), often resulting in poor functional outcomes. However, no existing model can specifically predict HAI in AIS patients. Therefore, we employed t...
SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI.
Scientific reports
Dec 28, 2024
Cerebral microbleeds (CMB) represent a feature of cerebral small vessel disease (cSVD), a prominent vascular contributor to age-related cognitive decline, dementia, and stroke. They are visible as spherical hypointense signals on T2*- or susceptibili...
Fuzzy APPSS: A novel method for quantifying COVID-19 impact in India under triangular spherical fuzzy environment.
Scientific reports
Dec 28, 2024
In the current scenario, decision-making models are essential for analyzing real-world problems. To address the dynamic nature of these problems, fuzzy decision-making models have been proposed by various researchers. However, an advanced technique i...
A proficient approach for the classification of Alzheimer's disease using a hybridization of machine learning and deep learning.
Scientific reports
Dec 28, 2024
Alzheimer's disease (AD) is a neurodegenerative disorder. It causes progressive degeneration of the nervous system, affecting the cognitive ability of the human brain. Over the past two decades, neuroimaging data from Magnetic Resonance Imaging (MRI)...
Clinically validated classification of chronic wounds method with memristor-based cellular neural network.
Scientific reports
Dec 28, 2024
Chronic wounds are a syndrome that affects around 4% of the world population due to several pathologies. The COV-19 pandemic has enforced the need of developing new techniques and technologies that can help clinicians to monitor the affected patients...
A machine learning tool for early identification of celiac disease autoimmunity.
Scientific reports
Dec 28, 2024
Identifying which patients should undergo serologic screening for celiac disease (CD) may help diagnose patients who otherwise often experience diagnostic delays or remain undiagnosed. Using anonymized outpatient data from the electronic medical reco...
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