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Related Concept Videos

Cross-Sectional Research01:50

Cross-Sectional Research

In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
Convenience Sampling Method00:55

Convenience Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Data Collection by Observations01:08

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...
Data Collection by Survey01:07

Data Collection by Survey

The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
Applications of Life Tables01:22

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
Observational Studies01:11

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...

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Updated: May 24, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Simplifying Cohort Definition with a Conversational Query Builder.

Joaquim Vertentes Rosa1, Raquel Paradinha1, João Rafael Almeida1

  • 1IEETA / DETI, LASI, University of Aveiro, Portugal.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

We developed a modular conversational assistant to simplify defining patient cohorts for observational studies using clinical data. This framework enhances usability and reduces computational overhead for medical researchers.

Keywords:
ATLASchatbotcohortsconversational assistantobservational

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Published on: June 21, 2018

Area of Science:

  • Health Informatics
  • Observational Research Methods
  • Clinical Data Management

Background:

  • Secondary use of clinical data is crucial for observational studies but faces challenges.
  • Existing query builders improve cohort definition efficiency but can have steep learning curves.

Purpose of the Study:

  • To propose a modular conversational assistant framework to enhance the usability of observational studies.
  • To address limitations of current query-building tools in clinical data analysis.

Main Methods:

  • Development of a modular conversational assistant framework deployable as a JavaScript component.
  • Utilization of deterministic algorithms to minimize computational overhead.
  • Integration via configuration files for seamless incorporation into existing medical information systems.

Main Results:

  • The framework is designed for improved system usability in defining patient cohorts.
  • Deterministic algorithms aim to reduce computational demands.
  • Configuration-based integration facilitates adoption in diverse medical systems.

Conclusions:

  • The proposed framework offers a more user-friendly approach to conducting observational studies with clinical data.
  • Validation within the OHDSI ecosystem is planned to demonstrate real-world applicability.
  • This tool can enhance the efficiency and accessibility of real-world evidence generation.