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A diagnostic support system based on pain drawings: binary and k-disease classification of EDS, GBS, FSHD, PROMM, and a control group with Pain2D
Background and objectiveThe diagnosis of rare diseases (RDs) is often challenging due to their rarity, variability and the high number of individual...
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Classification of diabetic retinopathy severity level using deep learning
BackgroundDiabetic retinopathy (DR) is an eye disease developed due to long-term diabetes mellitus, which affects retinal damage. The treatment at...
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PFP-HOG: Pyramid and Fixed-Size Patch-Based HOG Technique for Automated Brain Abnormality Classification with MRI
Detecting neurological abnormalities such as brain tumors and Alzheimer’s disease (AD) using magnetic resonance imaging (MRI) images is an important...
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Establishment of Biliary Atresia Prognostic Classification System via Survival-Based Forward Clustering — A New Biliary Atresia Classification
ObjectivesTo develop a machine learning algorithm with prognosis data to identify different clinical phenotypes of biliary atresia (BA) and provide...
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The performance of the 2022 ACR/EULAR classification criteria for Takayasu’s arteritis as compared to the 1990 ACR classification criteria in a Chinese population
In this study, we studied the performance of the 2022 American College of Rheumatology (ACR)/ European Alliance of Associations for Rheumatology...
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Robust prostate disease classification using transformers with discrete representations
Purpose:Automated prostate disease classification on multi-parametric MRI has recently shown promising results with the use of convolutional neural...
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Classification of Caries Based on CBCT: A Deep Learning Network Interpretability Study
This study aimed to create a caries classification scheme based on cone-beam computed tomography (CBCT) and develop two deep learning models to...
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The role of flow cytometry in the classification of myeloid disorders
The World Health Organization classification (WHO-HAEM5) and the International Consensus Classification (ICC 2022) of myeloid neoplasms are based on...
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The contribution of prosody to machine classification of schizophrenia
We show how acoustic prosodic features, such as pitch and gaps, can be used computationally for detecting symptoms of schizophrenia from a single...
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Study on Fine-Grained Visual Classification of Low-Resolution Urinary Erythrocyte
The morphological analysis test item of urine red blood cells is referred to as “extracorporeal renal biopsy,” which holds significant importance for...
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A Novel Classification Model Using Optimal Long Short-Term Memory for Classification of COVID-19 from CT Images
The human respiratory system is affected when an individual is infected with COVID-19, which became a global pandemic in 2020 and affected millions...
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Binary classification with fuzzy logistic regression under class imbalance and complete separation in clinical studies
BackgroundIn binary classification for clinical studies, an imbalanced distribution of cases to classes and an extreme association level between the...
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Interpretable Radiomic Signature for Breast Microcalcification Detection and Classification
Breast microcalcifications are observed in 80% of mammograms, and a notable proportion can lead to invasive tumors. However, diagnosing...
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A hybrid deep CNN model for brain tumor image multi-classification
The current approach to diagnosing and classifying brain tumors relies on the histological evaluation of biopsy samples, which is invasive,...
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Heart failure classification using deep learning to extract spatiotemporal features from ECG
BackgroundHeart failure is a syndrome with complex clinical manifestations. Due to increasing population aging, heart failure has become a major...
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Japanese Classification of Esophageal Cancer, 12th Edition: Part I
This is the first half of English edition of Japanese Classification of Esophageal Cancer, 12th Edition that was published by the Japan Esophageal...
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Pulmonary Nodule Classification Using a Multiview Residual Selective Kernel Network
Lung cancer is one of the leading causes of death worldwide and early detection is crucial to reduce the mortality. A reliable computer-aided...
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DeepCSFusion: Deep Compressive Sensing Fusion for Efficient COVID-19 Classification
Worldwide, the COVID-19 epidemic, which started in 2019, has resulted in millions of deaths. The medical research community has widely used computer...
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Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness....
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A Multi-Stage Faster RCNN-Based iSPLInception for Skin Disease Classification Using Novel Optimization
Nowadays, skin cancer is considered a serious disorder in which early identification and treatment of the disease are essential to ensure the...
