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Free Text Prediction Algorithm for Appendicitis

NCT03414853 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 689

Last updated 2021-03-03

No results posted yet for this study

Summary

Computer-aided diagnostic software has been used to assist physicians in various ways. Text-based prediction algorithms have been trained on past medical records through data mining and feature analysis. Currently, all text-based machine learning prediction problem models have been built on extracted data with no research completed on free text based prediction algorithms. This study aims to determine the accuracy of a free text prediction algorithm in predicting the probability of appendicitis in patients presenting to the Emergency Department with abdominal pain and gastrointestinal symptoms.

Conditions

Interventions

DIAGNOSTIC_TEST

Free text prediction algorithm for appendicitis

A free-text prediction software that predicts the probability of acute appendicitis

Sponsors & Collaborators

  • National University Hospital, Singapore

    lead OTHER

Principal Investigators

  • Kee Yuan Ngiam, Dr · National University Hospital, Singapore

Eligibility

Min Age
21 Years
Max Age
99 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2017-12-04
Primary Completion
2019-07-01
Completion
2020-07-01

Countries

  • Singapore

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03414853 on ClinicalTrials.gov