Using advanced AI to improve diagnosis and treatment of Takotsubo syndrome
Official title: Implications of Spatiotemporal Deep Learning Neural Networks in Echocardiographic Diagnosis and Prognostication of Takotsubo Syndrome
Funded at University of Iowa · NIH-11004641 · Data updated 2026-11-12
This study is working on using smart computer technology to help doctors tell the difference between Takotsubo syndrome and heart attacks, so patients can get the right diagnosis and treatment faster and more accurately.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Iowa NIH-funded |
| Lab location | 1 site (Iowa City, United States) |
| Project start | January 1, 2024 |
| Project end | December 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $393,391 |
| NIH project number | 5R01HL171624-02 |
| Project ID | NIH-11004641 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with Takotsubo syndrome or those experiencing symptoms that may suggest this condition.
✕Less likely to help
Patients with conditions unrelated to Takotsubo syndrome or acute myocardial infarction may not benefit from this research.
What this research studies
This research focuses on enhancing the diagnosis and treatment of Takotsubo syndrome (TTS) using advanced artificial intelligence techniques. By developing a deep learning algorithm that analyzes echocardiographic data, the project aims to differentiate TTS from acute myocardial infarction in real-time. The researchers will utilize large datasets from multiple institutions to improve the accuracy and reliability of the AI model, which will also help in predicting patient outcomes and tailoring personalized treatment plans. Patients may benefit from more accurate diagnoses and better-targeted therapies based on their unique conditions.
Why it matters
Potential benefit: If successful, this research could lead to more accurate diagnoses and personalized treatment strategies for patients with Takotsubo syndrome.
How similar studies have gone: Previous research has shown promise in using AI for medical imaging, indicating that this approach could lead to significant advancements in the field.
Where this research is happening
-
University of Iowa
Iowa City, United States Active
Researchers
- Principal investigator: Wu, Xiaodong — University of Iowa
- Study coordinator: Wu, Xiaodong
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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.