Using artificial intelligence to reduce bleeding and clotting risks in patients with blood cancers.
Official title: Mitigating Hematologic Adverse Events in Patients with Myeloid Malignancies: A Novel Causal Artificial Intelligence Approach
Funded at Harvard Medical School · NIH-10940122 · Data updated 2026-11-12
This study is looking to make treatments safer and more effective for people with myeloid cancers like Acute Myeloid Leukemia by using smart technology to find out what personal factors might increase their risk of blood clots and bleeding, so they can get better, more tailored care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Harvard Medical School NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | July 1, 2024 |
| Project end | June 30, 2027 |
| Funding year | 2024 |
| Award (this year) | $813,042 |
| NIH project number | 1R01HL174679-01 |
| Project ID | NIH-10940122 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients aged 65 and older who are diagnosed with myeloid malignancies, particularly Acute Myeloid Leukemia.
✕Less likely to help
Patients with myeloid malignancies who are younger than 65 or those without significant risk factors for thrombosis or bleeding may not benefit from this research.
What this research studies
This research aims to improve the safety and treatment of patients with myeloid malignancies, such as Acute Myeloid Leukemia, by utilizing advanced artificial intelligence techniques. The study will analyze a wide range of clinical data to identify personalized risk factors for thrombosis and bleeding, which are common complications in these patients. By integrating various data sources, the researchers hope to create more accurate predictions and optimize treatment plans tailored to individual patient profiles. This approach seeks to enhance patient outcomes by mitigating the risks associated with these serious conditions.
Why it matters
Potential benefit: If successful, this research could significantly reduce the incidence of life-threatening bleeding and clotting events in patients with myeloid malignancies.
How similar studies have gone: Previous research has shown promise in using machine learning for risk prediction in various medical fields, suggesting that this approach could be effective in this context as well.
Where this research is happening
-
Harvard Medical School
Boston, United States Active
Researchers
- Principal investigator: Yu, Kun-Hsing — Harvard Medical School
- Study coordinator: Yu, Kun-Hsing
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.