Purpose: Nutritional status is an established driver of cancer outcomes, but there is an insufficient workforce of registered dietitians to meet patient needs for nutritional counseling. Artificial intelligence (AI) and machine learning (ML) afford the opportunity to expand access to guideline-based nutritional support.
Methods: An AI-based nutrition assistant called Ina was developed on the basis of a learning data set of >100,000 expert-curated interventions, peer-reviewed literature, and clinical guidelines, and provides a conversational text message-based patient interface to guide dietary habits and answer questions.
Background: Accurate measurement of dietary intake is vital for providing nutrition interventions and understanding the complex role of diet in health. Traditional dietary assessment methods are very resource intensive and burdensome to participants. Technology may help mitigate these limitations and improve dietary data capture.
View Article and Find Full Text PDFIntramolecular emission quenching of a photoexcited ruthenium(II) polypyridine by a covalently linked naphthalene diimide (NDI) has been measured in aqueous buffer both without and with calf thymus DNA. The complex consists of a Ru(2,2'-bipyridine)(2)(2,2'-bipyridine-5-carboxamide)(2+) electron donor covalently attached by way of a -CH(2)CH(2)CH(2)- linker to a 1,4,5,8-naphthalene diimide acceptor (Ru-NDI, 1). The NDI portion of the complex intercalates in calf thymus DNA, as indicated by the hypochromism of its optical absorbance bands and observation of an induced circular dichroism spectrum in the same region.
View Article and Find Full Text PDF