Technical Name |
Using Generative Deep Learning to Predict Drug ResponseSurvival,Automatically Match Clinical Trials for Advanced Lung Cancer. |
Project Operator |
Taipei Medical University |
Project Host |
陳震宇 |
Summary |
Our team utilizes clinical big dataadvanced AI to expedite optimal treatment guidanceidentify appropriate clinical trials for new drugs in lung cancer patients. Through multimodal prediction methods, we analyze pathology reportsprovide results in just 5 seconds. This approach minimizes treatment delaysenhances shared decision-making among patients, families,healthcare providers for advanced lung cancer. |
Scientific Breakthrough |
Our team combines state-of-the-art natural language BERT modelgenerative GPT technology to make important information in pathological reports clearensure the securityprivacy of medical data. Through high-quality healthcare big data, we generate personalized recommendations for optimal treatment drug combinationssuitable new drug clinical trials. This groundbreaking research achievement achieves excellent performance that surpasses international benchmarks. |
Industrial Applicability |
This technology has broad industrial applicabilityadvantages over international benchmarks. It offers rapid guidance for drug combinationsclinical trial recommendations. We are validating it clinicallyapplying for patents to expedite commercialization. We also plan to promote market application through technology transfer collaborations. Our target market is not limited to Taiwan we aim for international reachwidespread utilization. |
Keyword |
Advanced-stage Lung Cancer Treatment Clinical Shared Decision Support System Real-world Data Precision Medicine Clinical Trial Matching Generative Artificial Intelligence Natural Language Processing BERT Generative Pre-trained Transformer Large Language Model |