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Computational methods for automated analysis of corneal nerve images: Lessons learned from retinal fundus image analysis
(
Elsevier
, 2020 , Article Review)
Corneal and retinal imaging provide a descriptive view of the nerve and vessel structure present inside the human eye, in a non-invasive manner. This helps in ocular, or other, disease identification and diagnosis. However, ...
Smartphone-based diabetic retinopathy severity classification using convolution neural networks
(
Springer
, 2021 , Conference Paper)
With diabetes growing at an alarming rate, changes in the retina causes a condition called diabetic retinopathy which eventually leads to blindness. Early detection of diabetic retinopathy is the best way to provide good ...
Self-ChakmaNet: A deep learning framework for indigenous language learning using handwritten characters
(
Elsevier
, 2023 , Article)
According to UNESCO's Atlas of the World's Languages in Danger, 40% of the languages today are counted as endangered in the future. Indigenous languages are endangered because of the less availability of interactive learning ...
Estimating Blood Glucose Levels Using Machine Learning Models with Non-Invasive Wearable Device Data
(
IOS Press BV
, 2023 , Conference Paper)
In 2019 alone, Diabetes Mellitus impacted 463 million individuals worldwide. Blood glucose levels (BGL) are often monitored via invasive techniques as part of routine protocols. Recently, AI-based approaches have shown the ...
AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
(
Ain Shams University
, 2023 , Article)
Internet of Things (IoT) and Artificial Intelligence (AI) technologies are currently replacing the traditional methods of handling buildings, infrastructure, and facilities design, control, and maintenance due to their ...
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ...
Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
(
MDPI
, 2021 , Article)
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming ...
TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images
(
Springer Nature
, 2024 , Article)
Tuberculosis (TB) is a chronic infectious lung disease, which caused the death of about 1.5 million people in 2020 alone. Therefore, it is important to detect TB accurately at an early stage to prevent the infection and ...
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
(
Elsevier
, 2023 , Article)
Introduction: Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia). DM impacted 463 million individuals worldwide in ...
The utility of a deep learning-based approach in Her-2/neu assessment in breast cancer
(
Elsevier
, 2023 , Article)
IntroductionHER-2/neu is a protein present on the surface of specific cancer cells and has been linked to the development and progression of certain cancer types. It is present in 15 to 20% of breast cancers and is clinically ...