Description:

Our project aims to harness the capabilities of deep learning algorithms to develop a sophisticated system for identification and classification of kidney diseases/disorders from CT scans. One significant hurdle we face is the lack of annotated CT datasets, necessitating innovative approaches such as transfer learning or semi-supervised learning to mitigate data scarcity issues. Moreover, rigorous clinical validation studies are necessary to assess the model's performance and compliance with regulatory standards, thereby ensuring its safety and efficacy in real-world healthcare settings. By surmounting these challenges, we endeavor to furnish the field of healthcare with a powerful tool capable of facilitating early disease detection, tailoring personalized treatment strategies, and ultimately enhancing patient outcomes.