• For Clinicians: Healthcare providers can recommend this tool to patients who may benefit from clinical trials as a part of their treatment plan, thus expanding their treatment options.
• For Patients: Cancer patients looking to participate in clinical trials can use this tool to find trials that match their specific type of and stage of cancer, as well as other personal health criteria.
• For Researchers: Investigators in clinical studies can utilize the tool to recruit suitable candidates for their clinical trials, ensuring a better match between the trial requirements and the patient profiles.

• Complexity of Matching: The matching process may not cover all the nuances of a patient's medical condition or the eligibility criteria of clinical trials, which can sometimes be very complex.
• Data Privacy: When the authors of the paper "Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes" evaluated the Philter library, it removed 99.4% of PHI in the clinical notes. While impressive, it is not perfect and can sometimes miss edge cases.
• Large Files: This program currently struggles with processing and deidentifying large files within a reasonable time. We're actively working on addressing this issue.

The efficacy of the application in assisting end-stage cancer patients relies on the advanced capabilities of the GPT-4 model, which has been trained on a diverse range of texts for comprehensive understanding and generation of human-like text. User feedback and iterative improvements are crucial for enhancing the application's performance.

I'm Venkata Chengalvala, the main developer of this app. As an AI consultant for Health Universe, I port high-quality peer-reviewed AI models helpful to clinicians, patients, and/or researchers to Health Universe's platform. I have a Bachelor of Science in Molecular, Cellular, and Developmental Biology (MCDB) and Computer Science from the University of Michigan-Ann Arbor. During my education, I engaged in medical research, co-authoring a literature review on tumor-derived exosomes, cited by 30+ people so far: https://www.sciencedirect.com/science/article/pii/S2211383521001398.

I developed this app to help clinicians match patients to suitable clinical trials. Currently, the matching process requires intense manual effort and can be infeasible for many providers. My aim is to streamline this, help patients get matched to clinical trials, and accelerate life-saving clinical research.

Your insights and feedback on this app are greatly appreciated. If you have any thoughts or feedback on this app, feel free to leave a comment below.