Role of artificial intelligence in critical care nutrition support and research Review
| Authors: | Kittrell, H. D.; Shaikh, A.; Adintori, P. A.; McCarthy, P.; Kohli-Seth, R.; Nadkarni, G. N.; Sakhuja, A. |
| Review Title: | Role of artificial intelligence in critical care nutrition support and research |
| Abstract: | Nutrition plays a key role in the comprehensive care of critically ill patients. Determining optimal nutrition strategy, however, remains a subject of intense debate. Artificial intelligence (AI) applications are becoming increasingly common in medicine, and specifically in critical care, driven by the data-rich environment of intensive care units. In this review, we will examine the evidence regarding the application of AI in critical care nutrition. As of now, the use of AI in critical care nutrition is relatively limited, with its primary emphasis on malnutrition screening and tolerance of enteral nutrition. Despite the current scarcity of evidence, the potential for AI for more personalized nutrition management for critically ill patients is substantial. This stems from the ability of AI to integrate multiple data streams reflecting patients' changing needs while addressing inherent heterogeneity. The application of AI in critical care nutrition holds promise for optimizing patient outcomes through tailored and adaptive nutrition interventions. A successful implementation of AI, however, necessitates a multidisciplinary approach, coupled with careful consideration of challenges related to data management, financial aspects, and patient privacy. © 2024 American Society for Parenteral and Enteral Nutrition. |
| Keywords: | treatment outcome; mortality; review; hypophosphatemia; quality control; vomiting; food and drug administration; food intake; fever; pneumonia; intensive care; acute kidney failure; hypotension; intensive care unit; hospitalization; intensive care units; total quality management; microarray analysis; artificial intelligence; heart failure; sepsis; health care system; thorax radiography; malnutrition; therapy; critical care; tachycardia; predictive value; prevention and control; hypernatremia; artificial ventilation; respiratory failure; critical illness; enteral nutrition; enteric feeding; artificial neural network; parenteral nutrition; critically ill patient; nutrition; visual acuity; lung edema; nutritional support; procedures; glycemic control; decision tree; machine learning; nutritional assessment; natural language processing; learning algorithm; tachypnea; nutrition assessment; speech discrimination; humans; human; sequential organ failure assessment score; deep learning; deep reinforcement learning; chatgpt; positive end expiratory pressure ventilation |
| Journal Title: | Nutrition in Clinical Practice |
| Volume: | 39 |
| Issue: | 5 |
| ISSN: | 0884-5336 |
| Publisher: | Sage Publications |
| Date Published: | 2024-10-01 |
| Start Page: | 1069 |
| End Page: | 1080 |
| Language: | English |
| DOI: | 10.1002/ncp.11194 |
| PUBMED: | 39073166 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Review -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PubMed and PDF -- Source: Scopus |
