AIMC Topic: Nutrition Assessment

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Prognostic value of combining nutritional inflammatory index trajectories and tumor characteristics in cervical cancer.

BMC women's health
OBJECTIVE: This investigation seeks to examine how varying longitudinal patterns in nutritional inflammatory index (NII) correlate with clinical outcomes in cervical cancer patients, while developing predictive models for prognosis.

Predicting malnutrition in PLWHIV using machine learning in gondar, Ethiopia.

BMC public health
BACKGROUND: Human Immunodeficiency Virus (HIV) continues to be a major global public health challenge, affecting 39.9 million people globally by the end of 2023. Sub-Saharan Africa bears a significant burden, contributing to 67% of cases. Malnutritio...

Association between geriatric nutritional risk index (GNRI) and asthma in elderly individuals aged 60 and above: a cross-sectional study of the NHANES 2005-2018.

BMC pulmonary medicine
OBJECTIVE: The geriatric nutritional risk index (GNRI) is a promising tool for predicting nutrition-related complications in older adults. This study aimed to explore the association between GNRI and asthma in individuals aged 60 and above.

Data-driven nutritional assessment of urban food landscapes: insights from Boston, London, and Dubai.

Scientific reports
Urban food landscapes significantly influence dietary habits and health outcomes, with disparities in food access contributing to obesity, particularly in socioeconomically disadvantaged neighborhoods. This study presents a data-driven approach to as...

An artificial intelligence malnutrition screening tool based on electronic medical records.

Clinical nutrition ESPEN
BACKGROUND & AIMS: Nutrition screening is a fundamental step to ensure appropriate intervention in patients with malnutrition. An automatic tool of nutritional risk screening based on electronic health records will improve efficiency and elevate the ...

Reasoning-Driven Food Energy Estimation via Multimodal Large Language Models.

Nutrients
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.)
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
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
: 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...