AIMC Topic: Malnutrition
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Deep learning is necessary for safety regulation in predicting malnutrition in gastric cancer patients.
Clinical nutrition (Edinburgh, Scotland)
Aug 2, 2024
Role of artificial intelligence in critical care nutrition support and research.
Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition
Jul 28, 2024
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 medic...
Artificial Intelligence in Malnutrition: A Systematic Literature Review.
Advances in nutrition (Bethesda, Md.)
Jul 4, 2024
Malnutrition among the population of the world is a frequent yet underdiagnosed problem in both children and adults. Development of malnutrition screening and diagnostic tools for early detection of malnutrition is necessary to prevent long-term comp...
Predictive model for assessing malnutrition in elderly hospitalized cancer patients: A machine learning approach.
Geriatric nursing (New York, N.Y.)
Jun 15, 2024
BACKGROUND: Malnutrition is prevalent among elderly cancer patients. This study aims to develop a predictive model for malnutrition in hospitalized elderly cancer patients.
Applying generative AI with retrieval augmented generation to summarize and extract key clinical information from electronic health records.
Journal of biomedical informatics
Jun 14, 2024
BACKGROUND: Malnutrition is a prevalent issue in aged care facilities (RACFs), leading to adverse health outcomes. The ability to efficiently extract key clinical information from a large volume of data in electronic health records (EHR) can improve ...
Validation of an Artificial Intelligence-Based Ultrasound Imaging System for Quantifying Muscle Architecture Parameters of the Rectus Femoris in Disease-Related Malnutrition (DRM).
Nutrients
Jun 8, 2024
(1) Background: The aim was to validate an AI-based system compared to the classic method of reading ultrasound images of the rectus femur (RF) muscle in a real cohort of patients with disease-related malnutrition. (2) Methods: One hundred adult pati...
Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017-18.
PloS one
May 31, 2024
AIM: Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most...
Development and evaluation of a deep learning framework for the diagnosis of malnutrition using a 3D facial points cloud: A cross-sectional study.
JPEN. Journal of parenteral and enteral nutrition
May 26, 2024
BACKGROUND: The feasibility of diagnosing malnutrition using facial features has been validated. A tool to integrate all facial features associated with malnutrition for disease screening is still demanded. This work aims to develop and evaluate a de...
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence.
Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition
Apr 9, 2024
The rapid surge in artificial intelligence (AI) has dominated technological innovation in today's society. As experts begin to understand the potential, a spectrum of opportunities could yield a remarkable revolution. The upsurge in healthcare could ...
The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information.
Clinical nutrition (Edinburgh, Scotland)
Apr 5, 2024
BACKGROUND & AIMS: The key step of the Global Leadership Initiative on Malnutrition (GLIM) is nutritional risk screening, while the most appropriate screening tool for colorectal cancer (CRC) patients is yet unknown. The GLIM diagnosis relies on weig...
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