MindMap Gallery Epidemiology—descriptive research
Descriptive research in epidemiology is the most basic type of epidemiological research methods. It is mainly used to describe the distribution of diseases or health conditions and exposure factors in the population. The purpose is to propose causal hypotheses and provide clues for further investigation and research. It is the basis of analytical research.
Edited at 2023-12-21 15:05:47This is a panoramic infographic—currently sweeping across the web—illustrating the comprehensive applications of OpenClaw, a popular open-source AI agent platform. It systematically introduces this intelligent agent framework—affectionately dubbed "Lobster Farming"—helping readers quickly grasp its core value, technical features, application scenarios, and security protocols. It serves as an excellent introductory guide and practical manual.
這是一張最近風靡全網關於熱門開源AI代理平台OpenClaw的全網應用全景圖解。它系統性地介紹了這款被稱為「養龍蝦」的智慧體框架,幫助讀者快速理解其核心價值、技術特性、應用場景及安全規範,是一份極佳的入門指南與實操手冊。此圖主要針對希望利用AI建構自動化工作流程的技術從業人員、中小企業主及效率追求者,透過9大模組層層遞進,全面剖析了OpenClaw從概念到落地的整個過程。 圖中核心內容首先釐清了「養龍蝦」指涉的是OpenClawd開源智能體,並強調其本質是「AI基建」而非一般聊天機器人。隨後詳細比較其與傳統AI助理的區別,擁有記憶管理、權限控制、會話隔離和異常恢復四大基礎能力,支援跨平台存取和多模型相容(如GPT、Claude、Ollama)。同時,圖解提供了完整的部署方案(雲端/本地/Docker),並列舉了辦公室自動化、內容創作、資料收集等五大應用程式場景。此外,還展示了其火爆程度、政府與大廠佈局、安全部署建議及適合/不適合的人群分類。幫助你快速掌握OpenClaw技術架構與應用價值,指導個人或企業建構AI自動化系統,規避資料外洩與權限失控風險,是學習「執行式AI」轉型的權威參考圖譜。
本圖由萬興腦圖繪製,是針對IT研發崗位的結構化個人履歷模板,完整涵蓋求職核心資訊模組。基本資訊區包含姓名、電話、信箱、求職意願及GitHub連結;專業概要要求以2-3句提煉核心優勢;工作經驗以「公司A高級Java開發工程師」為例,以「透過(行動),達成(量化成果)」格式呈現微服務架構設計、系統效能優化、團隊技術規範制定等職責,公司B經歷則聚焦功能模組開發與Elasticsearch搜尋優化;技能專長分程式語言、後端框架、中介軟體、資料庫、容器雲等維度,清楚展示技術堆疊;專案成果以「電商平台秒殺系統」為例,說明技術棧、架構設計、個人貢獻(Redis Lua庫存原子扣減)及KPI;教育背景包含一流大學電腦專業學歷,以及AWS認證解決方案架構師、軟考中級軟體設計師證書。模板邏輯嚴謹,涵蓋IT研發求職全流程關鍵訊息,幫助求職者清晰、量化展示專業能力。
This is a panoramic infographic—currently sweeping across the web—illustrating the comprehensive applications of OpenClaw, a popular open-source AI agent platform. It systematically introduces this intelligent agent framework—affectionately dubbed "Lobster Farming"—helping readers quickly grasp its core value, technical features, application scenarios, and security protocols. It serves as an excellent introductory guide and practical manual.
這是一張最近風靡全網關於熱門開源AI代理平台OpenClaw的全網應用全景圖解。它系統性地介紹了這款被稱為「養龍蝦」的智慧體框架,幫助讀者快速理解其核心價值、技術特性、應用場景及安全規範,是一份極佳的入門指南與實操手冊。此圖主要針對希望利用AI建構自動化工作流程的技術從業人員、中小企業主及效率追求者,透過9大模組層層遞進,全面剖析了OpenClaw從概念到落地的整個過程。 圖中核心內容首先釐清了「養龍蝦」指涉的是OpenClawd開源智能體,並強調其本質是「AI基建」而非一般聊天機器人。隨後詳細比較其與傳統AI助理的區別,擁有記憶管理、權限控制、會話隔離和異常恢復四大基礎能力,支援跨平台存取和多模型相容(如GPT、Claude、Ollama)。同時,圖解提供了完整的部署方案(雲端/本地/Docker),並列舉了辦公室自動化、內容創作、資料收集等五大應用程式場景。此外,還展示了其火爆程度、政府與大廠佈局、安全部署建議及適合/不適合的人群分類。幫助你快速掌握OpenClaw技術架構與應用價值,指導個人或企業建構AI自動化系統,規避資料外洩與權限失控風險,是學習「執行式AI」轉型的權威參考圖譜。
本圖由萬興腦圖繪製,是針對IT研發崗位的結構化個人履歷模板,完整涵蓋求職核心資訊模組。基本資訊區包含姓名、電話、信箱、求職意願及GitHub連結;專業概要要求以2-3句提煉核心優勢;工作經驗以「公司A高級Java開發工程師」為例,以「透過(行動),達成(量化成果)」格式呈現微服務架構設計、系統效能優化、團隊技術規範制定等職責,公司B經歷則聚焦功能模組開發與Elasticsearch搜尋優化;技能專長分程式語言、後端框架、中介軟體、資料庫、容器雲等維度,清楚展示技術堆疊;專案成果以「電商平台秒殺系統」為例,說明技術棧、架構設計、個人貢獻(Redis Lua庫存原子扣減)及KPI;教育背景包含一流大學電腦專業學歷,以及AWS認證解決方案架構師、軟考中級軟體設計師證書。模板邏輯嚴謹,涵蓋IT研發求職全流程關鍵訊息,幫助求職者清晰、量化展示專業能力。
descriptive research
descriptive research
Features
Observation is the main research method, and no intervention measures are taken on the research subjects.
Exposures are not randomly assigned, and there is no control group at the beginning of the study
No causal inference can be made
type
Current situation study (cross-sectional study)
Purpose
Three-dimensional distribution describing a disease or health condition
Discover clues to the cause
Suitable for secondary prevention of diseases (early detection, early diagnosis, early treatment)
Identify high-risk groups
Evaluate the effectiveness of monitoring, prevention, and control measures
Features
Observational study, no intervention measures are taken on the research subjects
The allocation of exposure factors is not random and no control group is established
No causal inference can be made
Specific time (short time)
Causal inferences can be made about exposure factors (gender, race, age) inherent to the research subjects.
Replace or estimate past exposure with current exposure
condition
Exposure now correlates well with past conditions or has been shown to change little
Known trends in current exposure compared with the original exposure
Exposure to recalled past is highly unreliable
Repeat regularly to obtain incidence data
Generally not used for diseases of short duration
Type of Study
census
Purpose (census and census)
Need early detection, early diagnosis, early treatment
Understand the prevalence of chronic diseases and the distribution of acute infectious diseases
Understand the health level of residents
Understand the normal value ranges of various physiological and biochemical indicators
Applicable conditions
Diseases with higher prevalence
The disease detection method is simple and easy to implement, with high sensitivity and specificity
Have human, material and financial resources
When the survey scope is small and the number of people is small, census can be used directly
A certain census rate should be ensured (generally no less than 80%)
Census rate = number of people actually enumerated/number of people to be enumerated
advantage
Overall, no sampling error
Simultaneously investigate the distribution of multiple diseases and health conditions
Achieve "three morning" prevention
shortcoming
Not suitable for diseases with low prevalence and no easy diagnostic methods
The workload is heavy and it is inevitable that the inspection will be missed
Spending manpower and material resources
sample survey
in principle
randomization
Sample size is appropriate
advantage
Save human, financial and material resources
Small investigation workload
shortcoming
The design and implementation of sample surveys are complex
Duplication or omission of information is difficult to detect
The research object has too much variation and is not suitable for use.
Prevalence is too low to be applicable
Sample size is difficult to randomize and sufficient
Sampling method
simple random sampling
advantage
Simple and basic
Each object has an equal probability of being drawn
shortcoming
Difficult to implement when the overall volume is large
systematic sampling
advantage
Can sample without knowing the population
Easier to perform among live crowds
The sample distribution is relatively even and representative.
shortcoming
If the distribution of each unit in the population has a periodic trend, and the extraction interval happens to coincide with this period, deviation may occur.
cluster sampling
advantage
Save manpower and material resources
shortcoming
Sampling error is large
stratified sampling
Classification
be divided in portion
optimal allocation
advantage
accurate
shortcoming
Improper selection of stratification factors will lose the meaning of stratification
multi-stage sampling
advantage
Make full use of the advantages of each sampling method
shortcoming
Before sampling, it is necessary to understand the demographic information and characteristics of survey units at all levels.
Error size order
Cluster sampling > Simple random sampling > Systematic sampling > Stratified sampling
investigation method
Face-to-face interviews are the most reliable
Petitions, online surveys, telephone interviews, self-administered questionnaires, physical examinations and laboratory tests
Design and implementation
Clarify the purpose of the investigation
Determine the objects of investigation
Determine investigation type and method
Estimate sample size
Factors that determine sample size
Overall disease prevalence (π)
The smaller π, the larger the sample size required
Allowable error (d)
The smaller the allowed error, the larger the sample size
Significance level (a)
The smaller a is, the larger the sample size is
Calculation method
Metrological data (measurement)
n=4S*2/d*2
S: estimate of population standard deviation
d: Allowable error
Count data (rate)
n=Za*2PQ/d*2
P: estimated prevalence
Q:1-P
dallowable error
Determine study variables and design questionnaire
data collection
General registration and reporting
Letter survey
Clinical examination data
Data compilation and analysis
bias
Control Method
Improve research subject compliance and testing rates
Strictly follow sampling methods
Correct selection of measurement tools and methods
Statistical analysis to identify confounding factors
Possible biases in current situation surveys
selection bias
Bias caused by improper selection methods of research subjects
No response bias (response rate higher than 90%)
survivorship bias
information bias
Respondent bias
Investigator bias
measurement bias
Advantages and Disadvantages
advantage
Commonly used sample surveys
There is a naturally occurring contemporaneous control group from the same population so that the results are comparable
Multiple exposure factors can be observed simultaneously
shortcoming
It is difficult to determine the temporal relationship between cause and effect
Incidence data not available
Research subjects may be in the preclinical stage and mistakenly classified as normal.
case reportcase report
case series analysis case series analysis
case investigation case investigation
investigation method
Visits and on-site investigations
ecological studyecological study
Features
Instead of using individuals as the unit of observation and analysis, we use groups as the unit
Unable to know individual exposure-disease relationship
Descriptive research in broad strokes
use
Provide clues to the cause and generate hypotheses about the cause
Evaluate the effectiveness of population-based interventions
type
ecological comparative study
Ecological Trend Research
advantage
Save manpower and material resources
Research into unknown causes may provide clues to causes
The only research method available when individual exposure doses cannot be measured
Evaluation of population-based interventions
Ecological trend research can estimate the development trend of a certain disease
shortcoming
Ecological fallacy—exposure levels are not true for the individual
Confounding factors are difficult to control
Difficult to determine cause and effect