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Classification of Illness

Classification of Illness

The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...

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Updated: Jul 23, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

使用无监督机器学习进行手术后妄想症状的数据驱动分类.

Panyawut Sri-Iesaranusorn¹, Ryoichi Sadahiro^2,3, Syo Murakami³

¹Division of Information Science, Nara Institute of Science and Technology, Nara, Japan.

Frontiers in psychiatry

|July 13, 2023

概括

这项研究使用机器学习来识别癌症手术患者手术后痴呆症的不同表型. 结果显示了三种 Delirium 集群,两种 Subsyndromal Delirium 集群和一个失眠集群,有助于理解 Delirium 机制.

关键词:

K-表示集群.癌症手术癌症手术手术狂妄症评级表-修订-98-98年没有假设的分类分类.现象型现象型是一种现象型.术后狂妄症术后狂妄症

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科学领域:

医学研究医学研究
数据科学是数据科学.
在瘤学瘤学.

背景情况:

手术后妄 (POD) 缺乏全面的表型,阻碍了对其机制和管理的理解.
提出了无假设的症状分类,作为一种揭示潜在的妄想机制的方法.
以前对POD数据驱动表型的证据是有限的.

研究的目的:

在接受侵袭性癌症手术的患者中探索术后妄想表型.
使用数据驱动的,无监督的机器学习方法,以最小的先前假设.
为了识别与 Delirium 相关的不同症状集群和患者子组.

主要方法:

招募了286名接受选择性侵入性癌症切除的患者.
在手术后的5天内,每天评估妄症,使用妄症评分表-修订-98 (DRS-R-98).
应用K-意味着对DRS-R-98得分进行聚类,以导出症状特征和分类患者子组.

主要成果:

确定了四个关键症状特征:混合运动,认知/高阶思维与感知障碍,急性/时间反应和睡眠-清醒周期障碍.
根据症状概况,将91名妄想患者分为七个不同的亚组.
通过机器学习推导出三个 Delirium 集群,两个 Subsyndromal Delirium 集群和一个失眠集群.

结论:

在癌症手术后,无监督的机器学习成功地将患者划分为不同的妄想和亚症候群妄想集群.
确定的群体包括妄想症,亚综合征妄想症和失眠表型.
进一步验证和研究这些集群的病理生理学对于理解POD机制至关重要.