[HTML][HTML] Development and assessment of assisted diagnosis models using machine learning for identifying elderly patients with malnutrition: cohort study
X Wang, F Yang, M Zhu, H Cui, J Wei, J Li… - Journal of Medical …, 2023 - jmir.org
Background Older patients are at an increased risk of malnutrition due to many factors
related to poor clinical outcomes. Objective This study aims to develop an assisted …
related to poor clinical outcomes. Objective This study aims to develop an assisted …
[HTML][HTML] Machine learning-based prediction of in-hospital complications in elderly patients using GLIM-, SGA-, and ESPEN 2015-diagnosed malnutrition as a factor
SS Ren, MW Zhu, KW Zhang, BW Chen, C Yang… - Nutrients, 2022 - mdpi.com
Background: Malnutrition is prevalent in elderly inpatients and is associated with various
adverse outcomes during their hospital stay, but the diagnosis of malnutrition still lacks …
adverse outcomes during their hospital stay, but the diagnosis of malnutrition still lacks …
[HTML][HTML] Explainable AI for malnutrition risk prediction from m-health and clinical data
F Di Martino, F Delmastro, C Dolciotti - Smart Health, 2023 - Elsevier
Malnutrition is a serious and prevalent health problem in the older population, and
especially in hospitalised or institutionalised subjects. Accurate and early risk detection is …
especially in hospitalised or institutionalised subjects. Accurate and early risk detection is …
Malnutrition risk assessment in frail older adults using m-health and machine learning
F Di Martino, F Delmastro… - ICC 2021-IEEE …, 2021 - ieeexplore.ieee.org
Malnutrition represents a major public health con-cern worldwide, and it particularly harms
older adults since it is frequently associated with several chronic health disorders. It …
older adults since it is frequently associated with several chronic health disorders. It …
[HTML][HTML] Machine Learning-Based Prediction of Complications and Prolonged Hospitalization with the GLIM Criteria Combinations Containing Calf Circumference in …
SS Ren, KW Zhang, BW Chen, C Yang, R Xiao, PG Li… - Nutrients, 2023 - mdpi.com
Background and aims: Malnutrition is widely present and influences the prognosis of elderly
inpatients, so it is helpful to be able to identify it with a convenient method. However, in the …
inpatients, so it is helpful to be able to identify it with a convenient method. However, in the …
[HTML][HTML] Explainable artificial intelligence-based decision support system for assessing the nutrition-related geriatric syndromes
V Petrauskas, R Jasinevicius, G Damuleviciene… - Applied Sciences, 2021 - mdpi.com
The use of artificial intelligence in geriatrics is very promising and relevant, as the diagnosis
of a geriatric patient is a complex, experience-based, and time-consuming process that …
of a geriatric patient is a complex, experience-based, and time-consuming process that …
[HTML][HTML] Predicting malnutrition from longitudinal patient trajectories with deep learning
Malnutrition is common, morbid, and often correctable, but subject to missed and delayed
diagnosis. Better screening and prediction could improve clinical, functional, and economic …
diagnosis. Better screening and prediction could improve clinical, functional, and economic …
Artificial intelligence driven malnutrition diagnostic model for patients with acute abdomen based on GLIM criteria: a cross-sectional research protocol
W Ma, B Cai, Y Wang, L Wang, MW Sun, CD Lu… - BMJ open, 2024 - bmjopen.bmj.com
Background Patients with acute abdomen often experience reduced voluntary intake and a
hypermetabolic process, leading to a high occurrence of malnutrition. The Global …
hypermetabolic process, leading to a high occurrence of malnutrition. The Global …
[HTML][HTML] Artificial Intelligence in Malnutrition: A systematic literature review
SMW Janssen, Y Bouzembrak, B Tekinerdogan - Advances in Nutrition, 2024 - Elsevier
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 …
both children and adults. Development of malnutrition screening and diagnostic tools for …
[HTML][HTML] Protocol: Artificial intelligence driven malnutrition diagnostic model for patients with acute abdomen based on GLIM criteria: a cross-sectional research …
W Ma, B Cai, Y Wang, L Wang, MW Sun, CD Lu… - BMJ Open, 2024 - ncbi.nlm.nih.gov
Background Patients with acute abdomen often experience reduced voluntary intake and a
hypermetabolic process, leading to a high occurrence of malnutrition. The Global …
hypermetabolic process, leading to a high occurrence of malnutrition. The Global …