相关实验视频

Updated: Jun 20, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.2K

意大利西北部COVID-19住院患者的多病症分析:使用进化机器学习和卫生行政数据进行纵向研究

Dayana Benny1,2, Mario Giacobini3, Alberto Catalano1,4

  • 1Centre for Biostatistics, Epidemiology, and Public Health, Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.

JMIR public health and surveillance
|July 18, 2024
PubMed
概括

多种疾病增加了COVID-19的严重性风险. 机器学习识别了与住院相关的特定药物和疾病组合,有助于脆弱人群的风险评估.

关键词:
在ATC中,ATC是ATC.在 COVID-19 疫情中,在ICD的基础上,ICD是ICD.意大利意大利意大利意大利意大利意大利这就是SARS-CoV-2病毒.大数据就是大数据.冠状病毒冠状病毒病毒数据数据的数据数据的数据.数据分析数据分析数据分析数据挖掘是数据挖掘的一个方法.流行病学流行病学进化算法是一种进化算法.功能垃圾桶 功能垃圾桶功能工程的特点工程.健康数据健康数据长时间的COVID.纵向分析 纵向分析纵向分析是一种纵向分析.纵向研究是一种纵向研究.机器学习是机器学习.多病态性多病态性多种药房多种药房公共卫生公共卫生.风险评估 风险评估 风险评估进行风险评估,评估风险.严重程度的严重程度.稀疏的二进制数据稀疏的二进制数据.

更多相关视频

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.6K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.0K

相关概念视频

Classification of Illness01:17

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...
7.4K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
346
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
377
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

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:
121
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
225
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
206