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Deep Neural Networks for Image-Based Dietary Assessment
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Artificial intelligence in nutritional assessment and decision making.

Pierre Singer1,2,3, Michal Slavin Kish2,4, Orit Raphaeli1,4

  • 1Institute of Nutrition Research, General Intensive Care Department, Beilinson Hospital, Rabin Medical Center, Petah Tikva.

Current Opinion in Clinical Nutrition and Metabolic Care
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Summary

Artificial intelligence (AI) enhances clinical nutrition by improving patient assessment and decision support. AI integration offers personalized nutrition but requires careful monitoring for safety and efficacy.

Keywords:
ICUartificial intelligencedecision makingmachine learningnutritional assessmentsarcopenia

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Area of Science:

  • Clinical Nutrition
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Artificial intelligence (AI) is increasingly vital in clinical nutrition.
  • Physicians require advanced tools for nutritional assessment and complication prediction.

Purpose of the Study:

  • To review recent AI advancements in clinical nutrition.
  • To highlight AI's role in physician decision support for nutritional management.

Main Methods:

  • Analysis of large databases for screening and assessment.
  • Utilizing medical imaging (CT scans) for sarcopenia detection.
  • Employing machine learning for parenteral and enteral nutrition optimization.
  • Leveraging digital technologies for eating behavior monitoring.

Main Results:

  • AI improves nutritional screening and assessment via big data analysis.
  • CT image analysis aids in sarcopenia diagnosis and outcome prediction.
  • Machine learning-driven parenteral nutrition formulas outperform traditional methods in neonates.
  • AI predicts enteral feeding tolerance and success.
  • Digital tools enable passive monitoring of eating behaviors.

Conclusions:

  • AI can optimize every stage of clinical nutrition, from screening to decision-making.
  • Successful AI integration necessitates large datasets, data scientists, and advanced technology.
  • AI holds potential for personalized nutrition but requires vigilant oversight for patient safety.