Learning Based Disease Diagnosis

Learning-based disease diagnosis leverages machine learning, particularly deep learning, to improve the accuracy and efficiency of medical diagnoses. Current research focuses on applying convolutional neural networks (CNNs), including architectures like ResNet and MobileNet, often within ensemble models and employing transfer learning techniques to enhance performance across various diseases and data types. This approach holds significant promise for improving healthcare by enabling faster, more accurate diagnoses, potentially leading to earlier interventions and better patient outcomes, although challenges remain in addressing data imbalances and ensuring data privacy.