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Related Concept Videos

Classification of Illness01:17

Classification of Illness

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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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Pulmonary Hypertension: Classification and Pathogenesis01:30

Pulmonary Hypertension: Classification and Pathogenesis

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Pulmonary hypertension (PH) is a severe health condition in which the mean pulmonary arterial pressure increases to 25 mmHg or more, even when the body is at rest. This high pressure in the blood vessels that transport blood from the heart to the lungs can cause various symptoms, including shortness of breath, can lead to right heart failure, and significantly affect the overall quality of life.
There are various classifications for PH, each relating to different underlying causes and also...
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Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

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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:
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Classification of Leukocytes01:30

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Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...
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Asthma-II: Pathophysiology and Classification01:26

Asthma-II: Pathophysiology and Classification

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Asthma is a prevalent chronic respiratory condition marked by inflammation and hyperresponsiveness of the airways. Its pathophysiology involves complex interactions among inflammatory pathways, immune responses, and neural mechanisms.
Additionally, environmental and genetic factors play crucial roles in determining an individual's susceptibility to asthma and the severity of their condition.
Critical processes in asthma pathophysiology include:
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Classification of Epithelial Tissues: Overview01:22

Classification of Epithelial Tissues: Overview

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Epithelial tissues are classified according to the shape of the cells and the number of cell layers formed. Cell shapes can be squamous (flattened and thin), cuboidal (square-like, as wide as it is tall), or columnar (rectangular, taller than it is wide). Additionally, the nucleus shape helps identify the type of epithelial cells. Squamous cells have flattened disc-shaped nuclei, cuboidal cells have spherical nuclei, and columnar cells have elongated nuclei.
Based on the number of cell layers,...
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Related Experiment Video

Updated: Dec 30, 2025

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
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Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

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Using ensemble classification methods in lung cancer disease.

Mohamed Hosni, Juan M Carrillo-de-Gea, Ali Idri

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    |January 18, 2020
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    Summary
    This summary is machine-generated.

    Ensemble classification methods are increasingly used for lung cancer diagnosis, with decision trees being the most common technique. Future research should explore diverse methods and tasks for improved lung cancer detection.

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    Area of Science:

    • Medical Informatics
    • Computational Biology
    • Machine Learning in Healthcare

    Background:

    • Ensemble classification methods offer enhanced predictive accuracy by combining multiple models.
    • Lung cancer remains a leading cause of mortality, necessitating advanced diagnostic tools.

    Purpose of the Study:

    • To provide a comprehensive overview of ensemble classification methods applied to lung cancer.
    • To analyze trends, techniques, and applications in this research area.

    Main Methods:

    • Systematic review of ensemble classification in lung cancer research.
    • Analysis of publication trends, medical tasks, ensemble types, base classifiers, combination rules, datasets, and tools.

    Main Results:

    • Research on ensemble methods for lung cancer began in 2003, with a focus on diagnosis.
    • Homogeneous ensembles and decision tree classifiers are prevalent.
    • Weka is the most frequently used software tool.

    Conclusions:

    • Further research should address under-investigated medical tasks and explore heterogeneous ensembles.
    • Investigating novel classification methods and combination rules can advance lung cancer diagnostics.