利用变压器预测零点射击健康轨迹

IF 12.4 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Pawel Renc, Yugang Jia, Anthony E. Samir, Jaroslaw Was, Quanzheng Li, David W. Bates, Arkadiusz Sitek
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引用次数: 0

摘要

将现代机器学习与临床决策相结合,对于降低医疗保健日益增长的成本和复杂性大有可为。我们介绍了用于健康结果模拟的增强变压器(ETHOS),这是变压器深度学习架构的一种新型应用,用于分析高维、异构和偶发性健康数据。ETHOS 利用患者健康时间轴(PHTs)--健康事件的详细标记化记录--进行训练,利用零点学习方法预测未来的健康轨迹。ETHOS 无需标注数据和模型微调,是医疗分析基础模型开发的重大进步。ETHOS 能够模拟各种治疗路径,并考虑患者的特定因素,是优化护理和解决医疗服务偏差的工具。未来的发展将扩展 ETHOS 的功能,以纳入更广泛的数据类型和数据源。我们的工作展示了在医疗保健领域加速人工智能开发和部署的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Zero shot health trajectory prediction using transformer

Zero shot health trajectory prediction using transformer

Zero shot health trajectory prediction using transformer
Integrating modern machine learning and clinical decision-making has great promise for mitigating healthcare’s increasing cost and complexity. We introduce the Enhanced Transformer for Health Outcome Simulation (ETHOS), a novel application of the transformer deep-learning architecture for analyzing high-dimensional, heterogeneous, and episodic health data. ETHOS is trained using Patient Health Timelines (PHTs)—detailed, tokenized records of health events—to predict future health trajectories, leveraging a zero-shot learning approach. ETHOS represents a significant advancement in foundation model development for healthcare analytics, eliminating the need for labeled data and model fine-tuning. Its ability to simulate various treatment pathways and consider patient-specific factors positions ETHOS as a tool for care optimization and addressing biases in healthcare delivery. Future developments will expand ETHOS’ capabilities to incorporate a wider range of data types and data sources. Our work demonstrates a pathway toward accelerated AI development and deployment in healthcare.
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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