AIMC Topic: Deep Learning

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Nonproliferative diabetic retinopathy dataset(NDRD): A database for diabetic retinopathy screening research and deep learning evaluation.

Health informatics journal
OBJECTIVES: In this article, we provide a database of nonproliferative diabetes retinopathy, which focuses on early diabetes retinopathy with hard exudation, and further explore its clinical application in disease recognition.

Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep st...

Eichner classification based on panoramic X-ray images using deep learning: A pilot study.

Bio-medical materials and engineering
BACKGROUND: Research using panoramic X-ray images using deep learning has been progressing in recent years. There is a need to propose methods that can classify and predict from image information.

FDB-Net: Fusion double branch network combining CNN and transformer for medical image segmentation.

Journal of X-ray science and technology
BACKGROUND: The rapid development of deep learning techniques has greatly improved the performance of medical image segmentation, and medical image segmentation networks based on convolutional neural networks and Transformer have been widely used in ...

Brain Disorder Detection and Diagnosis using Machine Learning and Deep Learning - A Bibliometric Analysis.

Current neuropharmacology
BACKGROUND AND OBJECTIVE: Brain disorders are one of the major global mortality issues, and their early detection is crucial for healing. Machine learning, specifically deep learning, is a technology that is increasingly being used to detect and diag...

Connectome-based schizophrenia prediction using structural connectivity - Deep Graph Neural Network(sc-DGNN).

Journal of X-ray science and technology
BACKGROUND: Connectome is understanding the complex organization of the human brain's structural and functional connectivity is essential for gaining insights into cognitive processes and disorders.

Deep Learning-Based Prediction of Radiation Therapy Dose Distributions in Nasopharyngeal Carcinomas: A Preliminary Study Incorporating Multiple Features Including Images, Structures, and Dosimetry.

Technology in cancer research & treatment
Intensity-modulated radiotherapy (IMRT) is currently the most important treatment method for nasopharyngeal carcinoma (NPC). This study aimed to enhance prediction accuracy by incorporating dose information into a deep convolutional neural network (...

A Novel Deep Learning Model for Drug-drug Interactions.

Current computer-aided drug design
INTRODUCTION: Drug-drug interactions (DDIs) can lead to adverse events and compromised treatment efficacy that emphasize the need for accurate prediction and understanding of these interactions.

Deep learning approach for skin melanoma and benign classification using empirical wavelet decomposition.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Melanoma is a malignant skin cancer that causes high mortality. Early detection of melanoma can save patients' lives. The features of the skin lesion images can be extracted using computer techniques to differentiate early between melanom...