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Nutritional Status

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[Usefulness of the CONUT Score for Predicting the Risk of Surgical Site Infections].

Gan to kagaku ryoho. Cancer & chemotherapy
BACKGROUND: Surgical site infections(SSIs)occur at a high frequency in patients after rectal cancer surgery and are readily aggravated. Therefore, prophylactic measures for infections based on the evaluation of the patient's perioperative risk are ve...

Vitamin D deficiency among children aged 10-18 years in Sri Lanka.

The Ceylon medical journal
BACKGROUND: Vitamin D deficiency (VDD) and insufficiency (VDI) are public health problems in many countries, and limited data is available on the prevalence of VDD/VDI in Sri Lanka.

Predictors of Stroke Outcome Extracted from Multivariate Linear Discriminant Analysis or Neural Network Analysis.

Journal of atherosclerosis and thrombosis
AIM: The prediction of functional outcome is essential in the management of acute ischemic stroke patients. We aimed to explore the various prognostic factors with multivariate linear discriminant analysis or neural network analysis and evaluate the ...

Identifying key predictors of mortality in young patients on chronic haemodialysis-a machine learning approach.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: The mortality risk remains significant in paediatric and adult patients on chronic haemodialysis (HD) treatment. We aimed to identify factors associated with mortality in patients who started HD as children and continued HD as adults.

Precision nutrition: A systematic literature review.

Computers in biology and medicine
Precision Nutrition research aims to use personal information about individuals or groups of individuals to deliver nutritional advice that, theoretically, would be more suitable than generic advice. Machine learning, a subbranch of Artificial Intell...

A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND AND AIMS: Most nutritional assessment tools are based on pre-defined questionnaires or consensus guidelines. However, it has been postulated that population data can be used directly to develop a solution for assessing malnutrition. This s...

Applicability of machine learning techniques in food intake assessment: A systematic review.

Critical reviews in food science and nutrition
The evaluation of food intake is important in scientific research and clinical practice to understand the relationship between diet and health conditions of an individual or a population. Large volumes of data are generated daily in the health sector...

Towards personalized nutritional treatment for malnutrition using machine learning-based screening tools.

Clinical nutrition (Edinburgh, Scotland)
Early identification of patients at risk of malnutrition or who are malnourished is crucial in order to start a timely and adequate nutritional therapy. Yet, despite the presence of many nutrition screening tools for use in the hospital setting, ther...

An Innovative Machine Learning Approach to Predict the Dietary Fiber Content of Packaged Foods.

Nutrients
Underconsumption of dietary fiber is prevalent worldwide and is associated with multiple adverse health conditions. Despite the importance of fiber, the labeling of fiber content on packaged foods and beverages is voluntary in most countries, making ...

A Review of Digital Innovations for Diet Monitoring and Precision Nutrition.

Journal of diabetes science and technology
This article provides an up-to-date review of technological advances in 3 key areas related to diet monitoring and precision nutrition. First, we review developments in mobile applications, with a focus on food photography and artificial intelligence...