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Data Collection by Observations

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...

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Related Experiment Video

Updated: Sep 22, 2025

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Published on: November 14, 2018

Image-based data mining applies to data collected from children.

Lydia J Wilson¹, Abigail Bryce-Atkinson², Andrew Green²

¹St. Jude Children's Research Hospital, Department of Radiation Oncology, Memphis, TN, USA.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)

|May 24, 2022

Summary

This summary is machine-generated.

Image-based data mining (IBDM) is feasible for pediatric radiotherapy research. This method helps analyze radiation dose responses in children, informing future studies and treatment planning for improved outcomes.

Keywords:

Childhood cancer Deformable image registration Radiotherapy Voxel-based analysis

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Last Updated: Sep 22, 2025

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

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Published on: November 14, 2018

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

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Cortical Source Analysis of High-Density EEG Recordings in Children

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Published on: June 30, 2014

Area of Science:

Medical Physics
Radiation Oncology
Pediatric Oncology

Background:

Image-based data mining (IBDM) is a novel voxel-based method for analyzing radiation dose responses.
IBDM has been successfully applied to adult patient data.
Pediatric patients present unique anatomic variability and side effect profiles compared to adults.

Purpose of the Study:

To investigate the feasibility of applying Image-based data mining (IBDM) for pediatric analyses.
To assess IBDM's applicability in childhood radiotherapy research.

Main Methods:

Tested IBDM using CT images and dose distributions from 167 pediatric patients with primary brain tumors.
Assessed IBDM sensitivity to reference selection using four reference patients.
Quantified spatial normalization accuracy and performed dose comparisons with simplified and modified clinical dose distributions.

Main Results:

Spatial normalization and dose comparisons were insensitive to reference selection, with small discrepancies.
Dose comparisons identified significant differences (p < 0.01) in 81% of simplified and 100% of modified clinical dose distributions.
While Dice Similarity Coefficients (DSCs) for simplified doses were high (0.9-1.0), PPVs and DSCs were low (≤0.4) for modified clinical doses.

Conclusions:

Image-based data mining (IBDM) is a feasible method for childhood late-effects research.
Findings can inform cohort selection for pediatric radiotherapy dose-response studies.
IBDM may facilitate treatment planning to reduce toxicity and improve quality of life in childhood cancer survivors.