AIMC Topic: Diet

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Assessing the feasibility of a mobile health-supported clinical decision support system for nutritional triage in oncology outpatients using Arden Syntax.

Artificial intelligence in medicine
BACKGROUND: Nutritional screening procedures followed by regular nutrition monitoring for oncological outpatients are no standard practice in many European hospital wards and outpatient settings. As a result, early signs of malnutrition are missed an...

Broiler responses to digestible threonine at different ages: a neural networks approach.

Journal of animal physiology and animal nutrition
Three experiments were conducted with broiler chickens to evaluate the effects of digestible threonine (DThr) and crude protein (CP) on their performance at three different phases of age: 1-14, 15-28 and 29-42 days. The measured traits included the f...

Harnessing the fish gut microbiome and immune system to enhance disease resistance in aquaculture.

Fish & shellfish immunology
The increasing global reliance on aquaculture is challenged by disease outbreaks, exacerbated by antibiotic resistance, and environmental stressors. Traditional strategies, such as antibiotic treatments and chemical interventions, are becoming less e...

Associations of dietary patterns with serum 25(OH) vitamin D and serum anemia related biomarkers among expectant mothers: A machine learning based approach.

International journal of medical informatics
BACKGROUND: Machine learning algorithms (MLA) gained prominence in nutritional epidemiology for analyzing dietary associations and uncovering intricate patterns within data. We explored dietary patterns associated with serum iron biomarkers and vitam...

Predicting Stress, Anxiety, and Depression in Adult Men Based on Nutritional and Lifestyle Variables: A Comparative Analysis of Machine Learning Methods.

Journal of food science
Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these conditions is vital for targeted interventions. This study explores the potential of machine learning (ML) to...

NLP for computational insights into nutritional impacts on colorectal cancer care.

SLAS technology
Colorectal cancer (CRC) is one of the most prominent cancers globally, with its incidence rising among younger adults due to improved screening practices. However, existing algorithms for CRC prediction are frequently trained on datasets that primari...

DiMB-RE: mining the scientific literature for diet-microbiome associations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To develop a corpus annotated for diet-microbiome associations from the biomedical literature and train natural language processing (NLP) models to identify these associations, thereby improving the understanding of their role in health a...

Boosting Immunity Through Nutrition and Gut Health: A Narrative Review on Managing Allergies and Multimorbidity.

Nutrients
The increasing global burden of allergic diseases and multimorbidity underscores the urgent need for innovative strategies to strengthen immune health. This review explores the complex relationships among nutrition, gut microbiota, immune regulation,...

Artificial Intelligence-Based Diets: A Role in the Nutritional Treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease?

Journal of human nutrition and dietetics : the official journal of the British Dietetic Association
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health concern. Effective management of this condition relies heavily on lifestyle modifications and dietary interventions. In this study, we sought to e...