Browsing by Subject "Artificial intelligence--Medical applications."
Now showing items 1-7 of 7
-
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 ... -
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 ... -
Comparative analysis of machine learning models for the prediction of asthma disease among the cardiovascular disease patients
(Brac University, 2024-06)Cardiovascular diseases (CVD) are a leading cause of morbidity and mortality worldwide, and recent studies have highlighted a potential association between CVD and the development of asthma. Predicting the likelihood of ... -
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 ... -
Fetal plane classification from 2D-ultrasound images leveraging squeeze and excitation self-attention mechanism for feature recalibration in MedMamba
(Brac University, 2024-05)A fetal ultrasound is a safe pregnancy test that provides an image of the baby’s heart, head, and spine while also analyzing various aspects of its anatomy. Maternal-fetal ultrasound imaging is critical during pregnancy, ... -
Increasing artificial intelligence ability of Maya for better digital healthcare
(Brac University, 2021-01)The main objective of this case study is to understand what are step a digital medical health provider take to resolve their AI issues. How they manage their data, how they deliver service to the users. Mayalogy ltd is ... -
A semi-supervised federated learning approach leveraging pseudo-labeling for Knee Osteoarthritis severity detection
(Brac University, 2024-06)Within medical image analysis, appropriately classifying the extent of knee osteoarthritis is a significant obstacle, made more difficult by the scarcity of annotated data and strict privacy rules. Conventional approaches ...
