Academic Articles & Research Papers

Thyroid Ultrasound Appropriateness Identification Through Natural Language Processing of Electronic Health Records

Objective: To address thyroid cancer overdiagnosis, we aim to develop a natural language processing (NLP) algorithm to determine the appropriateness of thyroid ultrasounds (TUS). Patients and Methods: Between 2017 and 2021, we identified 18...

Growth and development in paediatric onset inflammatory bowel disease: Data analysis from the CEDATA registry.

Local, authentique, durable : la gastronomie entre ancrage territorial et dynamiques globales.

Since the early twenty-first century, ecological, economic, and geopolitical crises have intensified challenges related to food systems, reshaping dietary practices and individual relationships with the environment. Sustainable food consump...

Studying the causes of humidity fluctuations in food products within industrial environments

The production of processed foods and animal nutrition requires precise control over product characteristics to ensure consistent quality. Unexpected fluctuations in key parameters, particularly humidity, can lead to significant financial l...

Mechanism-guided mitigation of acrylamide in thermally processed foods: emerging technologies and analytical verification.

Beyond solute clearance: the kidney-gut-immune-nutrition axis in hemodialysis and peritoneal dialysis and a proposed framework for integrated risk stratification.

MoringaLeafNet: A multi-class leaf disease dataset for precision agriculture and deep learning researchMendeley Data

Moringa Oleifera, which has outstanding nutritional and health benefits, is prized around the world because its leaves are rich in essential vitamins, antioxidants, and minerals that support digestion, help the immune system, and fight infl...

A Soybean Classification Method Based on Data Balance and Deep Learning

Soybean is a type of food crop with economic benefits. Whether they are damaged or not directly affects the survival and nutritional value of soybean plants. In machine learning, unbalanced data represent a major factor affecting machine le...

An Automated Image-Based Dietary Assessment System for Mediterranean Foods

Goal: The modern way of living has significantly influenced the daily diet. The ever-increasing number of people with obesity, diabetes and cardiovascular diseases stresses the need to find tools that could help in the daily intake of the n...

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning SystemResearch in context

Summary: Background: Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it...

Machine Learning in Nutrition Research

Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and ...

Prognostic value of postoperative glucose-to-lymphocyte ratio and visceral fat index in non-diabetic gastric cancer patients: a mediation and modeling study.

Unraveling the relationship between key aroma components and sensory properties of fragrant peanut oils based on flavoromics and machine learning

Key aroma components of 33 fragrant peanut oils with different aroma types were screened by combined using flavoromics and machine learning. A total of 108 volatile compounds were identified and 100 kinds of them were accurately quantified,...

A machine-learning approach for predicting the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome

The present study aimed to explore the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome (PCOS) and predict an appropriate dosage schedule using a machine-learning approach. Data were obtained fro...

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets

Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...

A review of machine learning in obesity

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine lea...

Development of Machine Learning Models to Predict Compressed Sward Height in Walloon Pastures Based on Sentinel-1, Sentinel-2 and Meteorological Data Using Multiple Data Transformations

Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass express...

Modern breeding of root, tuber, and bulb crops to enhance food and nutritional security.

Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modul...

The Combined Value of the Prognostic Nutritional Index and Pan-Immune-Inflammation Value in Predicting Neoadjuvant Chemotherapy and Survival in Locally Advanced Colon Cancer: A Retrospective Study.