AIMC Topic: Malnutrition

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Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.

PloS one
Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of the affected extremities, often leading to permanent disability and stigma. Described as a disease of poverty, the impact of socioeconomic indicators ...

Association between muscle mass assessed by an artificial intelligence-based ultrasound imaging system and quality of life in patients with cancer-related malnutrition.

Nutrition (Burbank, Los Angeles County, Calif.)
INTRODUCTION: Emerging evidence suggests that diminished skeletal muscle mass is associated with lower health-related quality of life (HRQOL) in individuals with cancer. There are no studies that we know of in the literature that use ultrasound syste...

Prediction of malnutrition in kids by integrating ResNet-50-based deep learning technique using facial images.

Scientific reports
In recent times, severe acute malnutrition (SAM) in India is considered a serious issue as per UNICEF 2022 records. In that record, 35.5% of children under age 5 are stunted, 19.3% are wasted, and 32% are underweight. Malnutrition, defined as these t...

Prediction of undernutrition and identification of its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.

PloS one
BACKGROUND AND OBJECTIVES: Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. Thus, the objectives of this study are to develop an appropriate model for predicting ...

Predicting malnutrition-based anemia in geriatric patients using machine learning methods.

Journal of evaluation in clinical practice
BACKGROUND: Anemia due to malnutrition may develop as a result of iron, folate and vitamin B12 deficiencies. This situation poses a higher risk of morbidity and mortality in the geriatric population than in other age groups. Therefore, early diagnosi...

Health economic evaluation of an artificial intelligence (AI)-based rapid nutritional diagnostic system for hospitalised patients: A multicentre, randomised controlled trial.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: Malnutrition is prevalent among hospitalised patients, and increases the morbidity, mortality, and medical costs; yet nutritional assessments on admission are not routine. This study assessed the clinical and economic benefits of u...

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
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.)
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...