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Sodium Intake Estimation in Hospital Patients Using AI-Based Imaging: Prospective Pilot Study.

Jiwon Ryu1,2, Sejoong Kim2,3,4, Yejee Lim1,2

  • 1Hospital Medicine Center, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.

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Summary
This summary is machine-generated.

Artificial intelligence (AI)-based imaging can estimate hospitalized patients' sodium intake using food photographs. This AI method shows clinical significance, potentially eliminating the need for 24-hour urine sodium measurements.

Keywords:
AIAI imageageartificial intelligencedietdiet managementeHealthfood AIhospitalimage-to-textimagingpilot studysexsmart nutritionsodium intakeurinevalidation

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Nutritional Science

Background:

  • Accurate measurement of sodium intake is crucial for hospitalized patients.
  • Traditional methods can be burdensome and less precise.
  • Artificial intelligence (AI)-based imaging offers a novel approach to dietary assessment.

Purpose of the Study:

  • To evaluate the applicability of an AI-powered diet management system for assessing sodium content in hospital meals.
  • To determine the accuracy of AI-based imaging in estimating patient sodium intake compared to established methods.

Main Methods:

  • A hybrid AI model, incorporating You Only Look Once version 4 (YOLOv4) and ResNet-101, analyzed food images taken before and after meals.
  • Hyperspectral imaging techniques were employed for precise food quantity and sodium amount estimation.
  • 24-hour urine sodium (UNa) was used as the reference standard for sodium intake evaluation.

Main Results:

  • The AI algorithm (AI-Na) estimated a median daily sodium intake of 2022.7 mg per person.
  • A significant correlation was found between AI-Na and 24-hour UNa, despite some disparities.
  • Regression analysis identified patient factors influencing the AI-Na and 24-hour UNa relationship, leading to a predictive formula.

Conclusions:

  • AI-based imaging demonstrates clinical significance for estimating sodium intake in hospitalized patients.
  • This AI approach may obviate the need for 24-hour urine sodium measurements.
  • The accuracy of AI-derived sodium intake can be influenced by factors like diuretic use.