Browsing by Subject "Disease detection"
Now showing items 1-20 of 26
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Artificial intelligence in nephrology: detecting chronic kidney disease using neural network
(Brac University, 2024-05)Chronic kidney disease (CKD) is a significant global health concern, impacting more than 800 million people globally. Prompt identification and precise categorization are crucial for optimal therapy. The primary objective ... -
Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
(Brac University, 2024-01)Cancer is a complex and highly invasive disease that forms due to the abnormal growth of cells in any part of the body. A majority of cancers are unraveled and treated by incorporating advanced technology. However, ovarian ... -
Brain tumor sectionalization through semantic segmentation approach
(Brac University, 2024-10)Accurate brain tumor detection and segmentation from magnetic resonance imaging (MRI) scans are vital for effective diagnosis, treatment planning, and patient monitoring. However, manual segmentation is time-consuming ... -
Classification of potato and corn leaf diseases using deep learning
(Brac University, 2024-06)One of the major hindrances to sustainable agriculture and an imminent threat to food security is plant disease. Constantly monitoring a plant’s health and spotting the problems in it is quite painstaking because it ... -
Comparative analysis of efficient deep learning models for breast cancer identification using relevant genes
(BRAC University, 2024-10)Cancer remains a formidable global health challenge, with early detection critical in improving patient outcomes. In this context, applying deep learning techniques to relevant gene analysis has emerged as a promising ... -
A comprehensive hybrid framework for Parkinson’s disease detection: integrating handcraft features along with deep learning-based feature extraction with variational autoencoder and traditional machine learning techniques for classification
(BRAC University, 2024-10)Neurodegenerative disorders, such as Parkinson’s disease, present a significant medical challenge, necessitating innovative approaches for detection. This thesis introduces a comprehensive hybrid framework that combines ... -
Deep learning based early Glaucoma detection
(Brac University, 2024-01)Glaucoma is a severe eye condition that can lead to progressive vision impairment if left untreated. Diagnosis and monitoring of glaucoma at an initial stage is critical for effective treatment of the disease. However, ... -
Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
(Brac University, 2024-01)Adrenocortical Carcinoma (ACC) is a rare but highly lethal cancer that occurs in the adrenal cortex. Accurate diagnosis of ACC are vital in order to determine appropriate treatment strategies and predict patient outcomes. ... -
Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques
(Brac University, 2024-01)The preliminary and precise diagnosis of Alzheimer’s Disease is significant for the speedy management and intervention of the disorder. Numerous valuable tools such as Magnetic Resonance Imaging (MRI), Positron Emission ... -
Detection of pulmonary diseases from chest X-ray images using deep learning model
(BRAC University, 2024-10)Deep learning models are important in efficiently identifying different pulmonary diseases from Chest X-ray Images (CXRs). Pneumonia is one of the most common lung diseases that cause death. Especially, stage 4 pneumonia ... -
Disease detection system of mango leaves
(Brac University, 2023-12)This work aims to design and implement a disease detection system for mango leaves. We have proposed two design approaches for the disease detection system for mango leaves. From these two design approaches, we have ... -
An efficient deep learning approach to detect diabetic retinopathy : analysis and severity prediction
(Brac University, 2024-01)Diabetic retinopathy is one complicated eye complication of diabetes and considered one of the major causes of preventable blindness worldwide. Diabetic retinopathy occurs when high glucose levels in the blood damage ... -
An efficient deep learning-based approach for Glioblastoma detection from MRI images
(BRAC University, 2024-10)In essence, an abnormal increase of brain cells is referred to as a brain tumor. Tumors come in two varieties: benign (non-cancerous) and malignant (cancerous). Cancerous tumors can originate in the brain itself (Primary) ... -
Enhanced medical image analysis: leveraging CUDA for fast and accurate Pneumonia detection with optimized CNNs
(Brac University, 2024-05)Pneumonia, a known leading child killer and a general health burden, continues to be a major concern due to its high morbidity and mortality rates in the developing world, which calls for prompt and accurate diagnosis. ... -
Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
(Brac University, 2023-09)Skin Cancer is a cancer form that has become very prevalent in recent times and, if left untreated, has the potential to cause premature death. That is why early diagnosis and treatment are important to cure this disease. ... -
Exploring machine learning techniques for symptom-based detection of livestock diseases
(Brac University, 2024-05)Effective livestock monitoring ensures food security and sustainability in our rapidly growing world. However, proper cattle disease is still not taken seriously in our country. Even in the livestock industry, it has not ... -
Identifying malnutrition from facial features of children using deep dearning
(BRAC University, 2024-10)Malnutrition remains a significant global health issue, particularly affecting children, leading to severe developmental challenges. Current diagnostic methods are often inefficient, relying on time-consuming physical ... -
An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
(Brac University, 2024-01)Early detection of retinal diseases can help people avoid going completely or partially blind. In this research, we will be implementing an interpretable diagnosis of retinal diseases using a hybrid model containing ... -
Mango leaf disease detection using image processing
(Brac University, 2024)Bangladesh is an agricultural country and mango cultivation plays a significant role in the economy of Bangladesh. Mango trees are at risk of different kinds of leaf disease. As a result, it can be the reason for hindering ... -
Optimized deep learning model for plant disease detection using leaf images
(Brac University, 2024-10)Accurate and timely plant disease detection is very much essential in crop health and agricultural yield. The work below describes an improved deep learning model for the classification of plant diseases through images. ...
