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DDFC: deep learning approach for deep feature extraction and classification of brain tumors using magnetic resonance imaging in E-healthcare system
This research explores the use of gated recurrent units (GRUs) for automated brain tumor
detection using MRI data. The GRU model captures sequential patterns and considers …
detection using MRI data. The GRU model captures sequential patterns and considers …
Attention-guided neural network for early dementia detection using MRS data
Imaging bio-markers have been widely used for Computer-Aided Diagnosis (CAD) of
Alzheimer's Disease (AD) with Deep Learning (DL). However, the structural brain atrophy is …
Alzheimer's Disease (AD) with Deep Learning (DL). However, the structural brain atrophy is …
Brain tumor classification based on neural architecture search
Brain tumor is a life-threatening disease and causes about 0.25 million deaths worldwide in
2020. Magnetic Resonance Imaging (MRI) is frequently used for diagnosing brain tumors. In …
2020. Magnetic Resonance Imaging (MRI) is frequently used for diagnosing brain tumors. In …
A YOLOv3 deep neural network model to detect brain tumor in portable electromagnetic imaging system
This paper presents the detection of brain tumors through the YOLOv3 deep neural network
model in a portable electromagnetic (EM) imaging system. YOLOv3 is a popular object …
model in a portable electromagnetic (EM) imaging system. YOLOv3 is a popular object …
A deep learning model to classify and detect brain abnormalities in portable microwave based imaging system
Automated classification and detection of brain abnormalities like a tumor (s) in
reconstructed microwave (RMW) brain images are essential for medical application …
reconstructed microwave (RMW) brain images are essential for medical application …
Deep learning and its applications in nuclear magnetic resonance spectroscopy
Y Luo, X Zheng, M Qiu, Y Gou, Z Yang, X Qu… - Progress in Nuclear …, 2025 - Elsevier
Abstract Nuclear Magnetic Resonance (NMR), as an advanced technology, has widespread
applications in various fields like chemistry, biology, and medicine. However, issues such as …
applications in various fields like chemistry, biology, and medicine. However, issues such as …
Detection of pseudo brain tumors via stacked LSTM neural networks using MR spectroscopy signals
Magnetic resonance spectroscopy (MRS) is one of the non-invasive tools used in the
detection of brain tumors. MRS provides a metabolic profile about the brain. In this profile …
detection of brain tumors. MRS provides a metabolic profile about the brain. In this profile …
Air pollution and cardiorespiratory hospitalization, predictive modeling, and analysis using artificial intelligence techniques
Air pollution has a serious and adverse effect on human health, and it has become a risk to
human welfare and health throughout the globe. One of the major effects of air pollution on …
human welfare and health throughout the globe. One of the major effects of air pollution on …
Transfer learning-based classification comparison of stroke
RAJ Alhatemi, S Savaş - Computer Science, 2022 - dergipark.org.tr
One type of brain disease that significantly harms people's lives and health is stroke. The
diagnosis and management of strokes both heavily rely on the quantitative analysis of brain …
diagnosis and management of strokes both heavily rely on the quantitative analysis of brain …
[HTML][HTML] On Application of Lightweight Models for Rice Variety Classification and Their Potential in Edge Computing
Rice is one of the fundamental food items that comes in many varieties with their associated
benefits. It can be sub-categorized based on its visual features like texture, color, and shape …
benefits. It can be sub-categorized based on its visual features like texture, color, and shape …