ChildPath: Diagnose depression in pre-schoolers based on daily activities

Logeswaran Kirthika, J. Abeykoon
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Abstract

To determine depression in pre-schoolers and validation of identifying depression based on daily activities. A comprehensive literature search, interviews with accredited mental health practitioners and a survey was conducted to validate the background aspects and existing diagnosis theories to map out based on daily activities. The results of the evaluation suggest a gap around diagnosis of depression in pre-schoolers due to lack of awareness and its distinctive nature to adult depression. This establishes a need for depression status calculation mechanism based on analysis of daily activities using machine learning to examine behaviour and speech patterns. Further, rule-based machine learning, will be implemented to offer personalized treatment plans if diagnosed with a status of depression.
儿童路径:根据日常活动诊断学龄前儿童抑郁症
目的:确定学龄前儿童的抑郁症,并验证基于日常活动识别抑郁症的有效性。通过全面的文献检索、对认可的精神卫生从业人员的访谈和调查来验证背景方面和现有的诊断理论,以日常活动为基础绘制。评估结果表明,由于缺乏对学龄前儿童抑郁症的认识,以及学龄前儿童抑郁症与成人抑郁症的独特性质,学龄前儿童抑郁症的诊断存在差距。这建立了一种基于使用机器学习检查行为和语言模式的日常活动分析的抑郁状态计算机制的需求。此外,如果被诊断患有抑郁症,将实施基于规则的机器学习,以提供个性化的治疗计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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