在行政和调查数据上使用机器学习来预测自杀的想法和行为:一个系统的审查
Nibene H Somé1,2,3,4, Pardis Noormohammadpour1,4, Shannon Lange1,2,5
1Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada.
Frontiers in psychiatry
|March 19, 2024
概括
机器学习有效地预测自杀的想法和行为,性能因结果而异. 提升算法在预测自杀念头和自杀死亡方面表现出色,而神经网络在自杀企图方面更好.
科学领域:
- 计算精神病学是一种计算精神病学.
- 医疗保健中的人工智能
- 公共卫生信息学 公共卫生信息学
背景情况:
- 机器学习 (ML) 通过整合复杂的风险因素,为预防自杀提供了一种强大的方法.
- 最近的研究和评论强调了ML在自杀预测中的越来越重要的作用.
- 本研究系统地审查了使用行政和调查数据在自杀风险评估中的ML应用.
研究的目的:
- 系统地识别使用ML技术对自杀预测的行政和调查数据的研究.
- 总结ML模型在预测自杀思想和行为方面的性能指标.
- 列举文献中发现的自杀想法和行动的重大风险因素.
主要方法:
- 在2019年1月1日至2022年5月11日期间发表的研究中,在多个数据库 (PubMed,Medline,Embase,PsycINFO,Web of Science,CINAHL,AMED) 进行了全面的系统文献搜索.
- 如果符合资格标准,则包括最近三次系统审查的文章.
- 使用受体运行特征曲线 (AUC) 下的面积值来评估性能,通过ML方法和自杀结果 (思想,尝试,死亡) 进行总结.
主要成果:
- 搜索中从2,200个独特的记录中获得了104篇相关文章.
- ML算法对自杀想法和行为有很好的预测能力,AUC值在0.80至0.89.9之间.
- 提升算法在预测自杀想法和自杀死亡方面表现出色,而神经网络在自杀企图方面是有效的. 风险因素因数据源和人口而异.
结论:
- 在预测自杀风险方面,ML的有效性取决于所选择的算法和数据源.
- 研究结果为开发更准确,更定制的自杀预防ML模型提供了宝贵的见解.
- 进一步的研究可以通过考虑特定的数据特征和结果措施来完善ML方法.
相关概念视频
Steps in Outbreak Investigation
126
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
126
Surveys
14.8K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
14.8K
Data Collection by Survey
6.5K
The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
6.5K
Introduction To Survival Analysis
232
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
232
Statistical Package for the Social Sciences (SPSS)
319
The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
319
Kaplan-Meier Approach
136
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
136


