| Title: | Application of artificial intelligence in tumor diagnosis and treatment |
| Lead Institution: | First Affiliated Hospital of Zhengzhou University |
| Principal investigator: |
Application 98680
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About
Aims: we aim to provide a stable and widely applicable method for tumor diagnosis and treatment based on clinical big data combined with Artificial intelligence methods. Scientific rationale: Cancer is one of the leading causes of death worldwide, with 19.29 million new cancer cases in 2020, down 18.3% from a year earlier; in 2021, there were more than 20 million new cases of cancer worldwide. Cancer patients carry a heavy disease burden and have huge unmet needs. Artificial intelligence (AI) is important for risk prediction, early detection of diseases, diagnosis through sequencing and medical imaging, accurate prognosis, biomarker identification, and therapeutic target identification for new drug discovery. To this end, we analyzed and summarized the application of different artificial intelligence methods in tumor diagnosis and treatment, hoping to provide a stable and widely applicable method for tumor diagnosis and treatment based on clinical big data combined with AI methods. The study aims to demonstrate the feasibility of a new integrated AI diagnosis and treatment system and apply it in clinical practice. Project duration: Three years will be needed to complete this project. Public health impact: This project is expected to significantly improve cancer risk prediction and prevention, enhance the accuracy of cancer screening and diagnosis, better stratify cancer risk, and guide us to more accurately identify high-risk individuals, thereby helping cancer patients provide more precise treatment strategies. This research will make an important contribution to the prognosis of cancer patients and greatly reduce the burden of cancer patients.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 15215 | Total and regional fat-to-muscle mass ratio and risks of pan-cancer: a prospective cohort study | Ruizhi Wang (+14) | 2025 | BMC Medicine |
Enabling scientific discoveries that improve human health