Multiple Diseases Detection using Deep Learning
Early detection of preventive diseases can play a crucial role in timely intervention and management. It also assists in efficient distribution of resources in the healthcare sector. Many approaches involving various machine learning algorithms have been used. However, clinical-decision machine learning algorithms for medical imaging face challenges with interpretability and reliability.We will use multiple architectures like CNN and other models for detection of disease. We also implement the GRU model that has shown impressive results on smaller datasets.
We endeavour to develop a system that facilitates early detection of multiple critical diseases using neural networks. We use different datasets for each of the diseases as per the need of the disease. We will present an easy to use GUI framework that allows anyone to access the model easily and derive results.