2023-11-27 デューク大学(Duke)
A new algorithm can accurately recreate the forces at work within a specific heart’s geometry based on smartwatch data alone. The technology could go a long way toward predicting people’s risks of heart disease and heart attack over long periods of time. Credit: BioHues Digital
◆この手法は、時間の経過に伴う病気の進行を考慮する上で、従来の方法よりも進化しています。LHMFは計算コストを削減し、クラウドコンピューティングを活用して、長期間にわたる心臓の血流ダイナミクスを効果的にシミュレートできることが示されています。この手法により、個々の人の心臓病や心臓発作のリスクを予測する技術が進展し、既存の記録を桁違いに上回る結果が得られました。
<関連情報>
- https://pratt.duke.edu/news/measuring-long-term-heart-stress-dynamics-with-smartwatch-data/
- https://dl.acm.org/doi/10.1145/3581784.3607101
クラウドコンピューティングによるウェアラブル駆動縦断血行動態マップの実現 Cloud Computing to Enable Wearable-Driven Longitudinal Hemodynamic Maps
Cyrus Tanade,Emily Rakestraw,William Ladd,Erik Draeger,Amanda Randles
SC ’23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis Published:11 November 2023
DOI:https://doi.org/10.1145/3581784.3607101
ABSTRACT
Tracking hemodynamic responses to treatment and stimuli over long periods remains a grand challenge. Moving from established single-heartbeat technology to longitudinal profiles would require continuous data describing how the patient’s state evolves, new methods to extend the temporal domain over which flow is sampled, and high-throughput computing resources. While personalized digital twins can accurately measure 3D hemodynamics over several heartbeats, state-of-the-art methods would require hundreds of years of wallclock time on leadership scale systems to simulate one day of activity. To address these challenges, we propose a cloud-based, parallel-in-time framework leveraging continuous data from wearable devices to capture the first 3D patient-specific, longitudinal hemodynamic maps. We demonstrate the validity of our method by establishing ground truth data for 750 beats and comparing the results. Our cloud-based framework is based on an initial fixed set of simulations to enable the wearable-informed creation of personalized longitudinal hemodynamic maps.
