Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Introduction to R

Introduction to R

R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's functionality,...

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

[Evaluation of Radiograph Accuracy in Skull X-ray Images Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi·2022

Same author

A Highly Sensitive and Stable rGO:MoS<sub>2</sub>-Based Chemiresistive Humidity Sensor Directly Insertable to Transformer Insulating Oil Analyzed by Customized Electronic Sensor Interface.

ACS sensors·2021

Same author

The effect of breast density on the missed lesion rate in screening digital mammography determined using an adjustable-density breast phantom tailored to Japanese women.

PloS one·2021

Same author

Evaluation of dose reduction potential in scatter-corrected bedside chest radiography using U-net.

Radiological physics and technology·2020

Same author

Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

Japanese journal of radiology·2020

Same author

Development of a deep learning model to identify hyperdense MCA sign in patients with acute ischemic stroke.

Japanese journal of radiology·2019

Same journal

[Multicenter Online Evaluation of IGRT Irradiation Position Accuracy Using an EPID-based End-to-end Postal Audit].

Nihon Hoshasen Gijutsu Gakkai zasshi·2026

Same journal

[Connecting Beyond Boundaries].

Nihon Hoshasen Gijutsu Gakkai zasshi·2026

Same journal

[The Forefront of Image Information Sharing between Medical Facilities].

Nihon Hoshasen Gijutsu Gakkai zasshi·2026

Same journal

[14. The Role of Radiological Technology Science in Targeted Radionuclide Therapy: Integrating Radiation Safety, Quantitative Imaging, and Dosimetry].

Nihon Hoshasen Gijutsu Gakkai zasshi·2026

Same journal

[Introduction of "JIRA Activity in 2026"].

Nihon Hoshasen Gijutsu Gakkai zasshi·2026

Same journal

[6. Data Literacy (4): Important Things to Keep in Mind When Analyzing Data].

Nihon Hoshasen Gijutsu Gakkai zasshi·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

[Fundamental knowledge for computer-aided diagnosis: Feature analysis using R]

¹Niigata University, Japan.

Nihon Hoshasen Gijutsu Gakkai Zasshi

|February 2, 2011

Summary

No abstract available in PubMed .

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Related Experiment Videos

Last Updated: Jun 4, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025