The problem ORGANELLO solves

The organ donation system faces significant challenges in efficiently and accurately matching organ donors with recipients. The primary issues include prolonged waiting times for patients, suboptimal matching due to the complexity of medical compatibility, and high rates of organ wastage when suitable matches are not found in time. These problems can lead to decreased transplant success rates and increased patient morbidity and mortality.

Key Challenges:
Prolonged Waiting Times:

Patients often endure extended periods on waiting lists due to the difficulty in finding suitable organ matches.
This delay can result in the deterioration of patients' health, reducing their chances of a successful transplant.
Complex Matching Process:

Matching donors and recipients involves evaluating numerous factors, including blood type, tissue compatibility, and the urgency of the recipient's condition.
The manual nature of the current matching process can be slow and prone to errors, leading to suboptimal matches.
High Organ Wastage:

Due to the perishable nature of organs, time is a critical factor. Delays in finding matches can result in organs being discarded because they are no longer viable.
Efficient and timely matching is essential to ensure that donated organs are utilized effectively.
Variability in Transplant Success Rates:

Inconsistent matching criteria and processes can lead to variability in transplant outcomes.
Finding the best possible match for each recipient is crucial to maximize the chances of a successful transplant and long-term health.
The AI-Driven Organ Donation Matching System aims to address these challenges by leveraging advanced technologies to streamline and enhance the matching process. By doing so, it seeks to reduce waiting times, improve match accuracy, minimize organ wastage, and ultimately increase the success rates of organ transplants.

Challenges I ran into

The challenges i faced is integrating streamlit and code for ai ml