医疗资料模型:在医疗保健中的科学和实际应用
IEEE journal of biomedical and health informatics
|October 2, 2023
概括
本研究引入了一个变压器模型,用于从电子健康记录中学习患者的表述. 该模型改善了疾病预测,并使疾病发现和保险得分的新方法成为可能.
科学领域:
- 医疗信息学 医疗信息学
- 机器学习 机器学习
- 计算生物学 计算生物学
背景情况:
- 电子健康记录 (EHR) 包含有价值的患者纵向数据.
- 有效的代表性学习对于从复杂的EHR数据中提取见解至关重要.
- 现有的方法可能无法完全捕捉疾病进展的时间性质.
研究的目的:
- 开发一种新的非监督的代表性学习方法,用于EHRs.
- 创建包括人口统计和疾病数据的通用患者个人资料.
- 证明学习患者嵌入在下游任务中的实用性.
主要方法:
- 患者病史以疾病的时间序列表示.
- 使用基于变压器的神经网络进行无监督学习.
- 将人口参数集成到嵌入空间中.
- 在100多万患者的大型数据集上进行培训.
主要成果:
- 拟议的模型在诊断预测方面显著超过了最先进的方法.
- 开发了一种新的预兆疾病发现方法,帮助流行病学研究设计.
- 患者嵌入改善了保险评分任务中的绩效指标.
结论:
- 开发的患者简介模型为EHR代表性学习提供了一个强大的工具.
- 该模型有助于跨医学领域的知识转移.
- 应用程序在疾病预测,发现和风险评估方面取得了重大进展.
相关概念视频
Models of Health Promotion and Illness Prevention I
2.1K
A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
2.1K
Methods of Documentation VI: Case Management Model
592
The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...
For example, a patient with a chronic...
592
Pharmacokinetic Models: Comparison and Selection Criterion
96
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
96
Pharmacokinetic Models: Overview
761
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
761
Model Approaches for Pharmacokinetic Data: Physiological Models
65
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
65
Mechanistic Models: Compartment Models in Individual and Population Analysis
64
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
64


