Related Experiment Video
Updated: Feb 3, 2026
08:39
Culture of Bladder Cancer Organoids as Precision Medicine Tools
Published on: December 28, 2021
5.4K
An infrastructure for precision medicine through analysis of big data
Marco Moscatelli1, Andrea Manconi2, Mauro Pessina3
1Institute for Biomedical Technologies - National Research Council (CNR-ITB), via F.lli Cervi 93, Segrate, 20090, MI, Italy. marco.moscatelli@itb.cnr.it.
BMC Bioinformatics
|October 28, 2018
Summary
We developed an infrastructure to integrate diverse healthcare data for precision medicine. This system analyzes patient histories, enabling early disease detection and personalized treatment strategies.
Area of Science:
- Biomedical Informatics
- Computational Biology
- Precision Medicine
Background:
- Advancements in omics data and systems biology simulation drive precision medicine.
- Digitization of clinical records is crucial for collecting and aggregating heterogeneous healthcare data.
- Patient data sharing presents ethical, legal, and technological challenges.
Purpose of the Study:
- To present an infrastructure for integrating large volumes of heterogeneous biological data.
- To enable the extraction and aggregation of unstructured and semi-structured clinical data.
- To develop predictive models for biomedical purposes and support precision medicine.
Main Methods:
- Applied an infrastructure to integrate data from laboratory, pathological anatomy, and biopsy exams (2010-2016).
- Implemented algorithms for data security, privacy, and extraction of unstructured/semi-structured information.
- Developed three Bayesian classifiers to analyze free-text clinical examination reports.
Main Results:
- The infrastructure successfully integrated diverse clinical data sources.
- Algorithms enabled precise historical analysis of patient clinical activities.
- Bayesian classifiers demonstrated good accuracy in analyzing free-text data for disease presence and status.
Conclusions:
- The infrastructure facilitates the integration of anonymized, heterogeneous clinical data.
- Processed data supports historical analysis and statistical assessments for complex biomedical questions.
- This approach aids in predicting diseases and identifying early diagnostic markers for personalized medicine.
Related Concept Videos
01:12Analysis of Population Pharmacokinetic Data
753
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
753
01:13Overview of Microsoft Excel as a Data Analysis Tool
1.6K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.6K
03:37Uncertainty in Measurement: Accuracy and Precision
101.2K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
101.2K
01:17Performing a Simple Data Analysis using MS-Excel Function
1.0K
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
1.0K
01:12Statistical Software for Data Analysis and Clinical Trials
1.5K
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...
1.5K
01:24Data Reporting and Recording
5.4K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.4K