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Artificial Intelligence Model for Time Series Classification: Prediction of Delayed Balloon Expulsion Test Using

Myeongsook Seo1, Kiwon Yoon2, Kee Wook Jung3

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Summary
This summary is machine-generated.

This study introduces time-series integrated pressurized volume (TS-IPVs) and an AI model to predict delayed balloon expulsion (BE) test results. The novel TS-IPV approach accurately identifies BE test outcomes using high-resolution anorectal manometry data.

Keywords:
artificial intelligenceballoon expulsion testconstipationhigh‐resolution anorectal manometry

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Area of Science:

  • Gastroenterology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Previous integrated pressurized volume (IPV) methods did not account for chronological changes in anorectal force.
  • High-resolution anorectal manometry (HRAM) data offers temporal dynamics crucial for enhanced prediction.
  • Time-series IPVs (TS-IPVs) and an AI model were developed to leverage these dynamics.

Purpose of the Study:

  • To introduce time-series integrated pressurized volumes (TS-IPVs) for analyzing HRAM data.
  • To develop an artificial intelligence (AI)-based diagnostic model for predicting delayed balloon expulsion (BE) test results.
  • To enhance the accuracy of BE test result prediction by incorporating temporal dynamics of anorectal pressure.

Main Methods:

  • 300 constipated patients (130 male, 170 female) underwent HRAM and BE tests.
  • TS-IPVs were calculated during the push maneuver within specific anal canal intervals.
  • Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks were employed for prediction.

Main Results:

  • Delayed BE was observed in 53.1% of males and 28.8% of females.
  • The TS-IPV ratio between the upper 1cm and lower 3cm of the anal canal (TS-IPV13 ratio) was the optimal predictor.
  • The AI model achieved Area Under the Curve (AUC) values of 0.988 for females and 0.996 for males.

Conclusions:

  • The AI model accurately classified delayed BE test results with an overall AUC of 0.99.
  • TS-IPVs utilized time-variant HRAM pressure data throughout the push maneuver without data loss.
  • TS-IPV serves as a more reliable marker than conventional parameters for classifying delayed BE test results.