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Related Concept Videos

Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Clinical Trials: Overview01:11

Clinical Trials: Overview

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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Design Example: Application of Archimedes' Principle01:11

Design Example: Application of Archimedes' Principle

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Archimedes' principle is fundamental in analyzing the buoyant force and stability of floating bodies. In this example, a wooden block with a rectangular section floats in seawater. Based on the block's dimensions, its specific gravity and the specific weight of seawater are used to find the volume of water displaced and the center of buoyancy.
The volume of seawater displaced by the block is determined by first calculating the block's weight. This is done by multiplying the...
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Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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The Uncertainty Principle04:08

The Uncertainty Principle

33.1K
Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
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Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
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In Silico Clinical Trials for Cardiovascular Disease
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Principles and Pitfalls of Clinical Trials Design.

M K Jeffcoat

    Journal of Periodontology
    |March 15, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This review discusses clinical trial designs for periodontitis and gingivitis, emphasizing how protocol details impact results. Key aspects covered include controls, outcomes, sample size, and patient selection for effective periodontal research.

    Keywords:
    Clinical trialsexperimental designresearch design

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    Area of Science:

    • Periodontology
    • Clinical Trial Design

    Background:

    • Periodontitis and gingivitis clinical trials present complex design challenges.
    • Protocol specifics significantly affect observed effects, result generalizability, and clinical significance.

    Purpose of the Study:

    • To review critical aspects of clinical trial design in periodontology.
    • To provide guidance on selecting appropriate designs and protocols for periodontitis and gingivitis research.

    Main Methods:

    • Review of selected elements of clinical trial methodology.
    • Focus on experimental design, control groups, outcome measures, sample size determination, and patient recruitment strategies.
    • Emphasis on considerations specific to periodontitis trials.

    Main Results:

    • Experimental design choices profoundly influence trial outcomes.
    • Careful consideration of controls, outcomes, sample size, and patient selection is crucial for valid and generalizable results.
    • Specific challenges and best practices for periodontitis trials are highlighted.

    Conclusions:

    • Optimizing clinical trial design is essential for advancing the understanding and treatment of periodontal diseases.
    • Methodological rigor in trial design enhances the reliability and clinical impact of research findings.
    • This review offers a framework for designing robust periodontitis and gingivitis studies.