| Title: | Explore the possible relationship of brain diseases with combined genetic, functional genomic, clinical, and imaging data |
| Lead Institution: | University of Science and Technology of China |
| Principal investigator: |
Application 98327
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About
Our research project focus on finding out the cause brain diseases. We expect to figure out what causes brain diseases, and which particular group of people are more vulnerable to brain diseases. In recent decades, with the development of computer science, information technology and bio-science.We now have access to massive patient database, data like genetic data are also accessible and with the help of fast speed processors, we may deploy our statistical or machine learning models with a larger size on top of massive amount of data. This enables researchers to investigate in a greater depth and width. In detail, we adopt both conventional statistical theory using tools like non-parametric models and hypothesis tests along with machine learning models like reinforcement learning, neural networks and random forests. We expect the project to be a long term research, due to the complexity of the mechnism of brain diseases.We will continue to focus on the data and investigate deeply. As a result, we expect to reveal the relationship of the occurrence of diseases with the status of the patient.Also,we may the evaluate effectiveness of current medical treatment and give advice according to statistical results. And finally,we expect to produce a pre-trained model to predict the chance of a patient having a particular disease according to his or her current status,gene data and other related aspects. This will help the public in identifing potential patient, protecting vulnerable people, reliving the work load of doctors.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 15522 | CATI: A medical context-enhanced framework for diagnosis code assignment in the UK Biobank study | Yue Shen (+11) | 2025 | Artificial Intelligence in Medicine |
Enabling scientific discoveries that improve human health