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HEAR4Health:让计算机听觉成为现代医疗保健重要组成部分的蓝图。

HEAR4Health: a blueprint for making computer audition a staple of modern healthcare.

作者信息

Triantafyllopoulos Andreas, Kathan Alexander, Baird Alice, Christ Lukas, Gebhard Alexander, Gerczuk Maurice, Karas Vincent, Hübner Tobias, Jing Xin, Liu Shuo, Mallol-Ragolta Adria, Milling Manuel, Ottl Sandra, Semertzidou Anastasia, Rajamani Srividya Tirunellai, Yan Tianhao, Yang Zijiang, Dineley Judith, Amiriparian Shahin, Bartl-Pokorny Katrin D, Batliner Anton, Pokorny Florian B, Schuller Björn W

机构信息

EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany.

Centre for Interdisciplinary Health Research, University of Augsburg, Augsburg, Germany.

出版信息

Front Digit Health. 2023 Sep 12;5:1196079. doi: 10.3389/fdgth.2023.1196079. eCollection 2023.

Abstract

Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise AI technologies; first and foremost in the fields of medical imaging, but also in the use of wearables and other intelligent sensors. In comparison, computer audition can be seen to be lagging behind, at least in terms of commercial interest. Yet, audition has long been a staple assistant for medical practitioners, with the stethoscope being the quintessential sign of doctors around the world. Transforming this traditional technology with the use of AI entails a set of unique challenges. We categorise the advances needed in four key pillars: Hear, corresponding to the cornerstone technologies needed to analyse auditory signals in real-life conditions; Earlier, for the advances needed in computational and data efficiency; Attentively, for accounting to individual differences and handling the longitudinal nature of medical data; and, finally, Responsibly, for ensuring compliance to the ethical standards accorded to the field of medicine. Thus, we provide an overview and perspective of HEAR4Health: the sketch of a modern, ubiquitous sensing system that can bring computer audition on par with other AI technologies in the strive for improved healthcare systems.

摘要

近年来,数字医学研究迅速增加,旨在将传统医疗系统转变为能够充分应对当代挑战的现代、智能和多功能的等效系统。这引发了一波利用人工智能技术的应用浪潮;首先是在医学成像领域,也包括可穿戴设备和其他智能传感器的应用。相比之下,计算机听觉领域至少在商业利益方面似乎滞后。然而,听觉长期以来一直是医学从业者的主要辅助手段,听诊器是世界各地医生的典型标志。利用人工智能改变这项传统技术带来了一系列独特的挑战。我们将所需的进展分为四个关键支柱:“聆听”(Hear),对应于在现实生活条件下分析听觉信号所需的基础技术;“更快”(Earlier),针对计算和数据效率方面所需的进展;“细心”(Attentively),用于考虑个体差异并处理医学数据的纵向特性;最后是“负责”(Responsibly),以确保符合医学领域的道德标准。因此,我们概述并展望了“聆听促健康”(HEAR4Health):一个现代的、无处不在的传感系统的构想,该系统能够使计算机听觉在改善医疗系统的努力中与其他人工智能技术并驾齐驱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e86b/10520966/d5529090dff1/fdgth-05-1196079-g001.jpg

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