AIMC Topic: Nutrition Assessment
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Optimizing Nutritional Care with Machine Learning: Identifying Sarcopenia Risk Through Body Composition Parameters in Cancer Patients-Insights from the NUTritional and Sarcopenia RIsk SCREENing Project (NUTRISCREEN).
Nutrients
Apr 18, 2025
: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance A...
Reasoning-Driven Food Energy Estimation via Multimodal Large Language Models.
Nutrients
Mar 24, 2025
Image-based food energy estimation is essential for user-friendly food tracking applications, enabling individuals to monitor their dietary intake through smartphones or AR devices. However, existing deep learning approaches struggle to recognize a ...
Rapid and accurate identification and quantification of Lycium barbarum L. components: Integrating deep learning and NMR for nutritional assessment.
Food research international (Ottawa, Ont.)
Mar 15, 2025
Lycium barbarum L. (L. barbarum), revered for its nutritional and commercial value, exhibits variable nutritional contents depending on the consumption method. This study introduces an innovative approach, the Identification and Quantification of L.b...
Controlling nutritional status score predicts posthepatectomy liver failure: an online interpretable machine learning prediction model.
European journal of gastroenterology & hepatology
Mar 5, 2025
BACKGROUND AND AIMS: Posthepatectomy liver failure (PHLF) remains a severe complication after hepatectomy for hepatocellular carcinoma (HCC) and accurate preoperative evaluation and predictive measures are urgently needed. We investigated the impact ...
AI-Powered Analysis of Weight Loss Reports from Reddit: Unlocking Social Media's Potential in Dietary Assessment.
Nutrients
Feb 27, 2025
: The increasing use of social media for sharing health and diet experiences presents new opportunities for nutritional research and dietary assessment. Large language models (LLMs) and artificial intelligence (AI) offer innovative approaches to anal...
Machine learning based on nutritional assessment to predict adverse events in older inpatients with possible sarcopenia.
Aging clinical and experimental research
Feb 22, 2025
BACKGROUND: The accuracy of current tools for predicting adverse events in older inpatients with possible sarcopenia is still insufficient to develop individualized nutrition-related management strategies. The objectives were to develop a machine lea...
An Evaluation of ChatGPT for Nutrient Content Estimation from Meal Photographs.
Nutrients
Feb 7, 2025
: Advances in artificial intelligence now allow combined use of large language and vision models; however, there has been limited evaluation of their potential in dietary assessment. This study aimed to evaluate the accuracy of ChatGPT-4 in estimatin...
Preoperative blood and CT-image nutritional indicators in short-term outcomes and machine learning survival framework of intrahepatic cholangiocarcinoma.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Jan 30, 2025
BACKGROUND&AIMS: Intrahepatic cholangiocarcinoma (iCCA) is aggressive with limited treatment and poor prognosis. Preoperative nutritional status assessment is crucial for predicting outcomes in patients. This study aimed to compare the predictive cap...
Humans
Machine Learning
Postoperative Complications
Neoplasm Recurrence, Local
Cholangiocarcinoma
Bilirubin
Subcutaneous Fat
Hepatectomy
Bile Duct Neoplasms
Nutritional Status
Preoperative Period
Intra-Abdominal Fat
Serum Albumin
Aged
Survival Rate
Prognosis
Male
Retrospective Studies
Middle Aged
Tomography, X-Ray Computed
Nutrition Assessment
Female
Machine Learning Analysis of Nutrient Associations with Peripheral Arterial Disease: Insights from NHANES 1999-2004.
Annals of vascular surgery
Jan 30, 2025
BACKGROUND: Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis, affecting over 200 million people worldwide. The incidence of PAD is increasing due to the aging population. Common risk factors include smoking, diabetes, an...
Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.
BMC cardiovascular disorders
Jan 23, 2025
OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional indices for adverse cardiovascular events (ACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) using...
Decision Support Techniques
Biomarkers
Myocardial Infarction
Female
Risk Factors
Inflammation Mediators
Aged
Nutritional Status
Inflammation
Humans
Male
Treatment Outcome
Neural Networks, Computer
Middle Aged
Decision Trees
Machine Learning
Nutrition Assessment
Predictive Value of Tests
Risk Assessment
Percutaneous Coronary Intervention
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