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Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
(Brac University, 2022-01)
Due to our unhealthy diets and the consumption of enhanced cholesterol in our
daily lives, our health has become vulnerable and at risk of different types of cardiac
diseases. The most common of them is Myocardial ...
Skin disease detection and classification using deep learning
(Brac University, 2022-01)
Skin Diseases have been the primary focus of this study, as they are one of the
most lethal diseases if not diagnosed and treated early. The research will enable
the fields of Medical Science and Computer Science to ...
A comparative study of lung cancer prediction using deep learning
(Brac University, 2022-09)
At the point when cells in the body develop out of control, this is alluded to as
cancerous development. Lung cancer is the term used to depict cancer that starts
in the lungs. At first in the field, classifier-based ...
Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
(Brac University, 2022-09)
Chronic kidney disease, often called chronic kidney failure, is a steady decline of
renal function. Some of the most common reasons for kidney failure are cyst,
stone and tumor. There may be no symptoms of chronic renal ...
Diabetic retinopathy detection and classification by using deep learning
(Brac University, 2022-01)
Eyes are the most sensitive part of a human being and it is one of the most challenging
tasks for a computer-aided system to classify its diseases. Many visionthreatening
diseases such as, Glaucoma and Diabetic Retinopathy ...
An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
(Brac University, 2022-05)
Optical Coherence Tomography (OCT) is an effective approach for diagnosing retinal
problems that can be used in combination with traditional diagnostic testing
methods. We developed and implemented a deep Convolutional ...