Machine learning in suicide science: Applications and ethics
Machine learning in suicide science: Applications and ethics
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DOI：
10.1002/bsl.2392
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发表时间：
2019-05-01
影响因子：
1.4
通讯作者：
Ribeiro, Jessica D.
中科院分区：
文献类型：
--
作者：
Linthicum, Kathryn P.;Schafer, Katherine Musacchio;Ribeiro, Jessica D.
几十年来，我们预测自杀的能力一直保持在接近概率的水平。机器学习最近成为推进自杀科学的一个有前途的工具，特别是在自杀预测领域。本综述介绍了机器学习及其在自杀研究中的潜在应用。虽然只有少数研究将机器学习用于自杀预测，但迄今为止的结果表明，准确性和阳性预测值有了相当大的提高。算法集成到临床实践中的潜在障碍进行了讨论，以及随之而来的伦理问题。总体而言，机器学习方法有望实现准确、可扩展和有效的自杀风险检测;然而，许多关键问题和问题仍未得到探索。
For decades, our ability to predict suicide has remained at near-chance levels. Machine learning has recently emerged as a promising tool for advancing suicide science, particularly in the domain of suicide prediction. The present review provides an introduction to machine learning and its potential application to open questions in suicide research. Although only a few studies have implemented machine learning for suicide prediction, results to date indicate considerable improvement in accuracy and positive predictive value. Potential barriers to algorithm integration into clinical practice are discussed, as well as attendant ethical issues. Overall, machine learning approaches hold promise for accurate, scalable, and effective suicide risk detection; however, many critical questions and issues remain unexplored.