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Related Concept Videos

Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
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Data Reporting and Recording

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...
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The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and family,...

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Related Experiment Video

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Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation
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iDASH: integrating data for analysis, anonymization, and sharing.

Lucila Ohno-Machado1, Vineet Bafna, Aziz A Boxwala

  • 1Division of Biomedical Informatics, University of California San Diego, La Jolla, California 92093, USA. machado@ucsd.edu

Journal of the American Medical Informatics Association : JAMIA
|November 15, 2011
PubMed
Summary
This summary is machine-generated.

The iDASH Center provides privacy-preserving tools and algorithms for secure data sharing. It enables researchers to access data and computing resources, fostering hypothesis generation and testing.

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Area of Science:

  • Biomedical Computing
  • Health Informatics
  • Data Privacy

Background:

  • The National Institutes of Health (NIH) funds the iDASH (integrating data for analysis, anonymization, and sharing) Center.
  • iDASH focuses on developing algorithms and tools for privacy-preserving data sharing.

Purpose of the Study:

  • To facilitate secure sharing of biomedical and behavioral data.
  • To provide researchers with access to data, software, and high-performance computing environments.
  • To enable the generation and testing of new hypotheses through data access.

Main Methods:

  • Developing foundational privacy technology research.
  • Engineering collaborative tools for data sharing.
  • Utilizing a HIPAA-certified cloud for secure data storage and access.
  • Guiding research and development through Driving Biological Projects.

Main Results:

  • Established a privacy-preserving framework for data sharing.
  • Developed innovative tools for collaborative research.
  • Enabled secure data access within a HIPAA-certified environment.
  • Facilitated data sharing across different biological levels and health conditions.

Conclusions:

  • iDASH successfully implements its goal of providing researchers with essential resources for data analysis and hypothesis testing.
  • The Center's approach integrates privacy technology, collaborative engineering, and diverse research projects.
  • Training and dissemination efforts enhance data sharing practices among stakeholders.