Template:Infobox medical condition

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  1. Template:Infobox medical condition

Template:Infobox medical condition is a standardized infobox used on Wikipedia and other wikis running MediaWiki software to quickly summarize essential information about a medical condition. This article provides a comprehensive guide for beginners on understanding, using, and customizing this valuable template. This template is crucial for maintaining consistency across articles related to health and medicine, enhancing readability and providing readers with a concise overview of complex topics.

Purpose and Benefits

The primary purpose of the `Infobox medical condition` template is to present key facts about a medical condition in a visually appealing and easily digestible format. It serves several important benefits:

  • Standardization: Ensures a consistent layout and presentation of information across all articles on medical conditions, improving user experience.
  • Readability: Allows readers to quickly scan for essential details without having to read through lengthy prose.
  • Navigation: Provides links to related articles (e.g., specialties, causes, treatments), facilitating further exploration of the topic.
  • Data Aggregation: Facilitates the potential for data mining and analysis of medical information across the wiki. For instance, one could potentially query all articles using the infobox to identify trends in disease prevalence or treatment effectiveness.
  • Visual Appeal: An aesthetically pleasing infobox can make an article more engaging and accessible.

Basic Usage

To use the infobox, copy the template code (available at Template:Infobox medical condition) and paste it into the beginning of the article. Then, fill in the appropriate parameters with the relevant information. Here's a basic example:

```wiki

  1. Template:Infobox medical condition

Template:Infobox medical condition is a standardized infobox used on Wikipedia and other wikis running MediaWiki software to quickly summarize essential information about a medical condition. This article provides a comprehensive guide for beginners on understanding, using, and customizing this valuable template. This template is crucial for maintaining consistency across articles related to health and medicine, enhancing readability and providing readers with a concise overview of complex topics.

Purpose and Benefits

The primary purpose of the `Infobox medical condition` template is to present key facts about a medical condition in a visually appealing and easily digestible format. It serves several important benefits:

  • Standardization: Ensures a consistent layout and presentation of information across all articles on medical conditions, improving user experience.
  • Readability: Allows readers to quickly scan for essential details without having to read through lengthy prose.
  • Navigation: Provides links to related articles (e.g., specialties, causes, treatments), facilitating further exploration of the topic.
  • Data Aggregation: Facilitates the potential for data mining and analysis of medical information across the wiki. For instance, one could potentially query all articles using the infobox to identify trends in disease prevalence or treatment effectiveness.
  • Visual Appeal: An aesthetically pleasing infobox can make an article more engaging and accessible.

Basic Usage

To use the infobox, copy the template code (available at Template:Infobox medical condition) and paste it into the beginning of the article. Then, fill in the appropriate parameters with the relevant information. Here's a basic example:

```wiki Template loop detected: Template:Infobox medical condition ```

This code will produce an infobox displaying the information provided for each parameter.

Parameters Explained

The `Infobox medical condition` template has numerous parameters, allowing for a detailed summary of the condition. Here's a breakdown of the most commonly used parameters:

  • `name` (Required): The official name of the medical condition.
  • `image` (Optional): The filename of an image related to the condition. The image should be available on the wiki. Consider image licensing carefully.
  • `image_caption` (Optional): A caption for the image.
  • `caption` (Optional): A general caption for the entire infobox. Use sparingly.
  • `specialty` (Optional): The medical specialty most commonly associated with the condition (e.g., Cardiology, Neurology, Oncology). Link to the relevant specialty article.
  • `ICD10` (Optional): The International Classification of Diseases, 10th Revision (ICD-10) code for the condition. Linking to the relevant ICD-10 entry (if available) is recommended. ICD-10 is a globally used standard.
  • `ICD9` (Optional): The International Classification of Diseases, 9th Revision (ICD-9) code for the condition. Less frequently used now that ICD-10 is prevalent.
  • `OMIM` (Optional): The Online Mendelian Inheritance in Man (OMIM) number for the condition, if it has a genetic basis. OMIM provides comprehensive information on human genes and genetic disorders.
  • `MeSH` (Optional): The Medical Subject Headings (MeSH) identifier for the condition. MeSH is a controlled vocabulary thesaurus used for indexing articles in PubMed.
  • `symptoms` (Optional): A list of common symptoms associated with the condition. Use commas to separate symptoms.
  • `typical_onset` (Optional): Describes how the condition typically begins (e.g., "Gradual", "Sudden", "Insidious").
  • `duration` (Optional): The typical duration of the condition (e.g., "7–10 days", "Chronic", "Lifelong").
  • `complications` (Optional): Potential complications that can arise from the condition. Use commas to separate complications.
  • `treatment` (Optional): Common treatments for the condition.
  • `prevention` (Optional): Measures that can be taken to prevent the condition.
  • `frequency` (Optional): The prevalence of the condition in the population.
  • `mortality` (Optional): The mortality rate associated with the condition.
  • `diagnosis` (Optional): Methods used to diagnose the condition.
  • `differential` (Optional): Other conditions that may be confused with this one (differential diagnosis).
  • `cause` (Optional): The known or suspected cause(s) of the condition.
  • `risk_factors` (Optional): Factors that increase the risk of developing the condition.
  • `pathophysiology` (Optional): A brief explanation of the underlying mechanisms of the disease.
  • `radiography` (Optional): Results typically observed on imaging studies (e.g., X-rays, CT scans, MRIs).
  • `blood_tests` (Optional): Abnormalities typically observed in blood tests.
  • `medication` (Optional): Specific medications used to treat the condition.
  • `therapy` (Optional): Other therapies used to treat the condition (e.g., physical therapy, psychotherapy).
  • `pronosis` (Optional): The expected outcome of the condition.
  • `research` (Optional): Current research efforts related to the condition.
  • `website` (Optional): Link to a reputable website providing information about the condition (e.g., National Institutes of Health, Mayo Clinic).

Advanced Usage and Customization

  • Using Multiple Values: For parameters that accept multiple values (e.g., `symptoms`, `complications`), you can use a bulleted list within the parameter:

```wiki | symptoms =

  • Runny nose
  • Sore throat
  • Cough

```

  • Using Templates within the Infobox: You can embed other templates within the infobox to provide more detailed information. For example, you could use a `Template:Drugbox` template within the `medication` parameter to provide detailed information about a specific drug.
  • Conditional Formatting: While not directly supported within the template itself, you can use Lua modules to implement conditional formatting based on the values of certain parameters. This allows for dynamic changes to the infobox based on the specific condition. This requires more advanced wiki editing skills.
  • Customizing the Appearance: The appearance of the infobox (e.g., colors, fonts) is controlled by the template's CSS stylesheet. Modifying the stylesheet requires administrator privileges. Generally, it is best to stick to the default styling to maintain consistency.
  • Adding New Parameters: Adding new parameters to the template requires careful consideration. It's important to ensure that the new parameter is relevant to a significant number of medical conditions and that it doesn't introduce unnecessary complexity. Template editing should be done by experienced users.
  • Using `default value`: This syntax allows you to specify a default value for a parameter if the user doesn't provide one. For example: `| specialty = General practice` will display "Unknown" if the `specialty` parameter is not specified.
  • Linking to External Databases: Wherever possible, link to reputable external databases such as PubMed, MedlinePlus, and Orphanet.

Best Practices

  • Accuracy: Ensure that all information provided in the infobox is accurate and supported by reliable sources. Cite your sources appropriately in the article body.
  • Conciseness: Keep the information concise and to the point. The infobox is meant to be a summary, not a comprehensive treatise.
  • Neutrality: Present information in a neutral and unbiased manner. Avoid using language that could be interpreted as promotional or judgmental.
  • Consistency: Follow the established guidelines for using the template. Be consistent in the way you format and present information.
  • Completeness: Fill in as many relevant parameters as possible. A complete infobox provides a more useful overview of the condition.
  • Image Quality: Use high-quality, relevant images. Ensure the image has an appropriate license and copyright information.
  • Avoid Redundancy: Don't repeat information that is already covered in detail in the article body. The infobox should complement the article, not duplicate it.

Common Errors and Troubleshooting

  • Template Not Displaying: Check for syntax errors in the template code. Make sure that all required parameters are present. Clear your browser cache.
  • Incorrect Formatting: Double-check the syntax of the parameters. Make sure that you are using the correct delimiters (e.g., `=`, `|`).
  • Image Not Displaying: Ensure that the image file exists on the wiki and that the filename is spelled correctly. Check the image's licensing information.
  • Links Not Working: Verify that the links are valid and that the target articles exist. Use the correct wiki syntax for creating links (e.g., `Article Name`).
  • Infobox Too Wide: Reduce the number of parameters or use shorter captions. Consider using a smaller image.

Related Templates and Articles

Strategies, Technical Analysis, Indicators, and Trends (for context, relating to article readership)

While focusing on a medical template, understanding the broader context of information seeking is beneficial. Readers researching medical conditions often employ strategies similar to those in financial analysis. Here are some relevant concepts:

  • **Trend Analysis:** Identifying the increasing or decreasing incidence of a disease (similar to stock price trends).
  • **Risk Assessment:** Evaluating factors that increase susceptibility to a condition (akin to assessing investment risk).
  • **Correlation Analysis:** Investigating relationships between symptoms and diagnoses (similar to correlation in financial data).
  • **Statistical Significance:** Determining the reliability of medical research findings (analogous to statistical significance in trading).
  • **Data Visualization:** Using charts and graphs to represent medical data (like candlestick charts in finance).
  • **Moving Averages:** Tracking changes in disease prevalence over time (similar to moving averages in technical analysis).
  • **Support and Resistance Levels:** Identifying critical thresholds in disease progression (akin to support and resistance in trading).
  • **Breakout Patterns:** Recognizing sudden changes in disease outbreaks (similar to breakout patterns in stock prices).
  • **Volatility Analysis:** Assessing the unpredictability of a disease's course (analogous to volatility in financial markets).
  • **Regression Analysis:** Predicting future disease trends based on historical data (similar to regression analysis in finance).
  • **Fibonacci Retracements:** Identifying potential levels of disease recurrence (akin to Fibonacci retracements in trading).
  • **Bollinger Bands:** Measuring the range of normal disease values (similar to Bollinger Bands in technical analysis).
  • **Relative Strength Index (RSI):** Assessing the speed and change of disease progression (analogous to RSI in finance).
  • **MACD (Moving Average Convergence Divergence):** Identifying changes in the trend of disease incidence (similar to MACD in trading).
  • **Elliott Wave Theory:** Applying wave-like patterns to understand disease outbreaks (akin to Elliott Wave Theory in finance).
  • **Monte Carlo Simulation:** Modeling the potential spread of a disease (similar to Monte Carlo simulations in finance).
  • **Scenario Planning:** Developing strategies to cope with different disease scenarios (analogous to scenario planning in business).
  • **Sentiment Analysis:** Gauging public perception of a disease (similar to sentiment analysis in financial news).
  • **Time Series Analysis:** Analyzing disease data over time to identify patterns (similar to time series analysis in finance).
  • **Gap Analysis:** Identifying discrepancies in healthcare access or treatment (akin to gap analysis in business).
  • **Decision Tree Analysis:** Evaluating different treatment options (similar to decision tree analysis in finance).
  • **Bayesian Networks:** Modeling the probabilistic relationships between disease factors (analogous to Bayesian networks in risk assessment).
  • **Game Theory:** Analyzing interactions between patients, healthcare providers, and public health officials (similar to game theory in economics).
  • **Network Analysis:** Mapping the spread of infectious diseases (akin to network analysis in social science).
  • **Chaos Theory:** Understanding the unpredictable nature of complex biological systems (similar to chaos theory in physics).
  • **Swarm Intelligence:** Applying collective behavior models to disease control (analogous to swarm intelligence in robotics).

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This code will produce an infobox displaying the information provided for each parameter.

Parameters Explained

The `Infobox medical condition` template has numerous parameters, allowing for a detailed summary of the condition. Here's a breakdown of the most commonly used parameters:

  • `name` (Required): The official name of the medical condition.
  • `image` (Optional): The filename of an image related to the condition. The image should be available on the wiki. Consider image licensing carefully.
  • `image_caption` (Optional): A caption for the image.
  • `caption` (Optional): A general caption for the entire infobox. Use sparingly.
  • `specialty` (Optional): The medical specialty most commonly associated with the condition (e.g., Cardiology, Neurology, Oncology). Link to the relevant specialty article.
  • `ICD10` (Optional): The International Classification of Diseases, 10th Revision (ICD-10) code for the condition. Linking to the relevant ICD-10 entry (if available) is recommended. ICD-10 is a globally used standard.
  • `ICD9` (Optional): The International Classification of Diseases, 9th Revision (ICD-9) code for the condition. Less frequently used now that ICD-10 is prevalent.
  • `OMIM` (Optional): The Online Mendelian Inheritance in Man (OMIM) number for the condition, if it has a genetic basis. OMIM provides comprehensive information on human genes and genetic disorders.
  • `MeSH` (Optional): The Medical Subject Headings (MeSH) identifier for the condition. MeSH is a controlled vocabulary thesaurus used for indexing articles in PubMed.
  • `symptoms` (Optional): A list of common symptoms associated with the condition. Use commas to separate symptoms.
  • `typical_onset` (Optional): Describes how the condition typically begins (e.g., "Gradual", "Sudden", "Insidious").
  • `duration` (Optional): The typical duration of the condition (e.g., "7–10 days", "Chronic", "Lifelong").
  • `complications` (Optional): Potential complications that can arise from the condition. Use commas to separate complications.
  • `treatment` (Optional): Common treatments for the condition.
  • `prevention` (Optional): Measures that can be taken to prevent the condition.
  • `frequency` (Optional): The prevalence of the condition in the population.
  • `mortality` (Optional): The mortality rate associated with the condition.
  • `diagnosis` (Optional): Methods used to diagnose the condition.
  • `differential` (Optional): Other conditions that may be confused with this one (differential diagnosis).
  • `cause` (Optional): The known or suspected cause(s) of the condition.
  • `risk_factors` (Optional): Factors that increase the risk of developing the condition.
  • `pathophysiology` (Optional): A brief explanation of the underlying mechanisms of the disease.
  • `radiography` (Optional): Results typically observed on imaging studies (e.g., X-rays, CT scans, MRIs).
  • `blood_tests` (Optional): Abnormalities typically observed in blood tests.
  • `medication` (Optional): Specific medications used to treat the condition.
  • `therapy` (Optional): Other therapies used to treat the condition (e.g., physical therapy, psychotherapy).
  • `pronosis` (Optional): The expected outcome of the condition.
  • `research` (Optional): Current research efforts related to the condition.
  • `website` (Optional): Link to a reputable website providing information about the condition (e.g., National Institutes of Health, Mayo Clinic).

Advanced Usage and Customization

  • Using Multiple Values: For parameters that accept multiple values (e.g., `symptoms`, `complications`), you can use a bulleted list within the parameter:

```wiki | symptoms =

  • Runny nose
  • Sore throat
  • Cough

```

  • Using Templates within the Infobox: You can embed other templates within the infobox to provide more detailed information. For example, you could use a `Template:Drugbox` template within the `medication` parameter to provide detailed information about a specific drug.
  • Conditional Formatting: While not directly supported within the template itself, you can use Lua modules to implement conditional formatting based on the values of certain parameters. This allows for dynamic changes to the infobox based on the specific condition. This requires more advanced wiki editing skills.
  • Customizing the Appearance: The appearance of the infobox (e.g., colors, fonts) is controlled by the template's CSS stylesheet. Modifying the stylesheet requires administrator privileges. Generally, it is best to stick to the default styling to maintain consistency.
  • Adding New Parameters: Adding new parameters to the template requires careful consideration. It's important to ensure that the new parameter is relevant to a significant number of medical conditions and that it doesn't introduce unnecessary complexity. Template editing should be done by experienced users.
  • Using `default value`: This syntax allows you to specify a default value for a parameter if the user doesn't provide one. For example: `| specialty = Unknown` will display "Unknown" if the `specialty` parameter is not specified.
  • Linking to External Databases: Wherever possible, link to reputable external databases such as PubMed, MedlinePlus, and Orphanet.

Best Practices

  • Accuracy: Ensure that all information provided in the infobox is accurate and supported by reliable sources. Cite your sources appropriately in the article body.
  • Conciseness: Keep the information concise and to the point. The infobox is meant to be a summary, not a comprehensive treatise.
  • Neutrality: Present information in a neutral and unbiased manner. Avoid using language that could be interpreted as promotional or judgmental.
  • Consistency: Follow the established guidelines for using the template. Be consistent in the way you format and present information.
  • Completeness: Fill in as many relevant parameters as possible. A complete infobox provides a more useful overview of the condition.
  • Image Quality: Use high-quality, relevant images. Ensure the image has an appropriate license and copyright information.
  • Avoid Redundancy: Don't repeat information that is already covered in detail in the article body. The infobox should complement the article, not duplicate it.

Common Errors and Troubleshooting

  • Template Not Displaying: Check for syntax errors in the template code. Make sure that all required parameters are present. Clear your browser cache.
  • Incorrect Formatting: Double-check the syntax of the parameters. Make sure that you are using the correct delimiters (e.g., `=`, `|`).
  • Image Not Displaying: Ensure that the image file exists on the wiki and that the filename is spelled correctly. Check the image's licensing information.
  • Links Not Working: Verify that the links are valid and that the target articles exist. Use the correct wiki syntax for creating links (e.g., `Article Name`).
  • Infobox Too Wide: Reduce the number of parameters or use shorter captions. Consider using a smaller image.

Related Templates and Articles

Strategies, Technical Analysis, Indicators, and Trends (for context, relating to article readership)

While focusing on a medical template, understanding the broader context of information seeking is beneficial. Readers researching medical conditions often employ strategies similar to those in financial analysis. Here are some relevant concepts:

  • **Trend Analysis:** Identifying the increasing or decreasing incidence of a disease (similar to stock price trends).
  • **Risk Assessment:** Evaluating factors that increase susceptibility to a condition (akin to assessing investment risk).
  • **Correlation Analysis:** Investigating relationships between symptoms and diagnoses (similar to correlation in financial data).
  • **Statistical Significance:** Determining the reliability of medical research findings (analogous to statistical significance in trading).
  • **Data Visualization:** Using charts and graphs to represent medical data (like candlestick charts in finance).
  • **Moving Averages:** Tracking changes in disease prevalence over time (similar to moving averages in technical analysis).
  • **Support and Resistance Levels:** Identifying critical thresholds in disease progression (akin to support and resistance in trading).
  • **Breakout Patterns:** Recognizing sudden changes in disease outbreaks (similar to breakout patterns in stock prices).
  • **Volatility Analysis:** Assessing the unpredictability of a disease's course (analogous to volatility in financial markets).
  • **Regression Analysis:** Predicting future disease trends based on historical data (similar to regression analysis in finance).
  • **Fibonacci Retracements:** Identifying potential levels of disease recurrence (akin to Fibonacci retracements in trading).
  • **Bollinger Bands:** Measuring the range of normal disease values (similar to Bollinger Bands in technical analysis).
  • **Relative Strength Index (RSI):** Assessing the speed and change of disease progression (analogous to RSI in finance).
  • **MACD (Moving Average Convergence Divergence):** Identifying changes in the trend of disease incidence (similar to MACD in trading).
  • **Elliott Wave Theory:** Applying wave-like patterns to understand disease outbreaks (akin to Elliott Wave Theory in finance).
  • **Monte Carlo Simulation:** Modeling the potential spread of a disease (similar to Monte Carlo simulations in finance).
  • **Scenario Planning:** Developing strategies to cope with different disease scenarios (analogous to scenario planning in business).
  • **Sentiment Analysis:** Gauging public perception of a disease (similar to sentiment analysis in financial news).
  • **Time Series Analysis:** Analyzing disease data over time to identify patterns (similar to time series analysis in finance).
  • **Gap Analysis:** Identifying discrepancies in healthcare access or treatment (akin to gap analysis in business).
  • **Decision Tree Analysis:** Evaluating different treatment options (similar to decision tree analysis in finance).
  • **Bayesian Networks:** Modeling the probabilistic relationships between disease factors (analogous to Bayesian networks in risk assessment).
  • **Game Theory:** Analyzing interactions between patients, healthcare providers, and public health officials (similar to game theory in economics).
  • **Network Analysis:** Mapping the spread of infectious diseases (akin to network analysis in social science).
  • **Chaos Theory:** Understanding the unpredictable nature of complex biological systems (similar to chaos theory in physics).
  • **Swarm Intelligence:** Applying collective behavior models to disease control (analogous to swarm intelligence in robotics).

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