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Diagnosis of retinal damage using Resnet rescaling and support vector machine (Resnet-RS-SVM): a case study from an Indian hospital
PurposeThis study aims to address the challenge of identifying retinal damage in medical applications through a computer-aided diagnosis (CAD)...
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Development and Validation of a 3D Resnet Model for Prediction of Lymph Node Metastasis in Head and Neck Cancer Patients
The accurate diagnosis and staging of lymph node metastasis (LNM) are crucial for determining the optimal treatment strategy for head and neck cancer...
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Unified deep learning models for enhanced lung cancer prediction with ResNet-50–101 and EfficientNet-B3 using DICOM images
Significant advancements in machine learning algorithms have the potential to aid in the early detection and prevention of cancer, a devastating...
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An Automatic Framework for Nasal Esthetic Assessment by ResNet Convolutional Neural Network
Nasal base aesthetics is an interesting and challenging issue that attracts the attention of researchers in recent years. With that insight, in this...
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MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data
PurposeMedical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence,...
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Res-TransNet: A Hybrid deep Learning Network for Predicting Pathological Subtypes of lung Adenocarcinoma in CT Images
This study aims to develop a CT-based hybrid deep learning network to predict pathological subtypes of early-stage lung adenocarcinoma by integrating...
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An early detection and segmentation of Brain Tumor using Deep Neural Network
BackgroundMagnetic resonance image (MRI) brain tumor segmentation is crucial and important in the medical field, which can help in diagnosis and...
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3cDe-Net: a cervical cancer cell detection network based on an improved backbone network and multiscale feature fusion
BackgroundCervical cancer cell detection is an essential means of cervical cancer screening. However, for thin-prep cytology test (TCT)-based images,...
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Deep Inception-ResNet: A Novel Approach for Personalized Prediction of Cumulative Pregnancy Outcomes in Vitro Fertilization Treatment (IVF)
BackgroundInfertility is one of the major causes of socioeconomic stress worldwide due to social stigma and stressful lifestyles. Despite...
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Detection method of absence seizures based on Resnet and bidirectional GRU
BackgroundEpilepsy is a common chronic neurological disease. Its repeated seizure attacks have a great negative impact on patients’ physical and...
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Classification of neck tissues in OCT images by using convolutional neural network
Identification and classification of surrounding neck tissues are very important in thyroid surgery. The advantages of optical coherence tomography...
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Enhancing brain tumor detection in MRI images through explainable AI using Grad-CAM with Resnet 50
This study addresses the critical challenge of detecting brain tumors using MRI images, a pivotal task in medical diagnostics that demands high...
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Recognition of Digital Dental X-ray Images Using a Convolutional Neural Network
Digital dental X-ray images are an important basis for diagnosing dental diseases, especially endodontic and periodontal diseases. Conventional...
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Multi-Modal Feature Fusion-Based Multi-Branch Classification Network for Pulmonary Nodule Malignancy Suspiciousness Diagnosis
Detecting and identifying malignant nodules on chest computed tomography (CT) plays an important role in the early diagnosis and timely treatment of...
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Performance of novel deep learning network with the incorporation of the automatic segmentation network for diagnosis of breast cancer in automated breast ultrasound
ObjectiveTo develop novel deep learning network (DLN) with the incorporation of the automatic segmentation network (ASN) for morphological analysis...
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Non-invasive precise staging of liver fibrosis using deep residual network model based on plain CT images
PurposeThe aim of this study was to explore the application of five-class deep residual network models based on plain CT images and clinical features...
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Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets
BackgroundLow-dose computed tomography (LDCT) has been shown useful in early lung cancer detection. This study aimed to develop a novel deep learning...
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Self-supervised category selective attention classifier network for diabetic macular edema classification
AimsThis study aims to develop an advanced model for the classification of Diabetic Macular Edema (DME) using deep learning techniques. Specifically,...
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A multi-view fusion lightweight network for CRSwNPs prediction on CT images
Accurate preoperative differentiation of the chronic rhinosinusitis (CRS) endotype between eosinophilic CRS (eCRS) and non-eosinophilic CRS...
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SF-TMN: SlowFast temporal modeling network for surgical phase recognition
PurposeAutomatic surgical phase recognition is crucial for video-based assessment systems in surgical education. Utilizing temporal information is...
