This study presents an automated method for detecting and measuring the apex head thickness of tomato plants, a critical phenotypic trait associated with plant health, fruit development, and yield forecasting. Due to the apex's sensitivity to physical contact, non-invasive monitoring is essential. This …

This study shows dentists' perception of AI in the Netherlands and the reasons why they use or do not use AI yet

Introduction Recording sap flow in plants is essential to understanding water usage, especially for herbaceous species like tomatoes. While plant physiology research has progressed, there remains a gap in applying sap flow sensor data to these species. In this study, the predictive capabilities of Recurrent …

This review aimed to map the clinical readiness of artificial intelligence investigations focused on preventive dentistry.

Agriculture and horticulture are essential for ensuring safe food to the growing global population, but they also contribute significantly to climate change and biodiversity loss due to the extensive use of chemicals. Integrated pest management is currently employed to monitor and control pest populations, …

Consistency issues limit the sharing of horticultural data across multiple systems, resulting in challenges for users to analyze data effectively across various systems utilizing artificial intelligence technology. Introducing data governance principles can help standardize and unify data practices, …

In dit onderzoek is gekeken naar voorbeelden uit de literatuur vanuit verschillende gezondheidsdisciplines. Verschillende studies pasten machine learning (vaak deep learning) toe voor de vroegdetectie van ziekten op basis van beschikbare data uit het elektronisch patiëntendossier (EPD). Het bleek dat …

The paper introduced an automatic score detection model using object detection techniques. The performance of sevenmodels belonging to two different architectural setups was compared. Models like YOLOv8n, YOLOv8s, YOLOv8m, RetinaNet-50, and RetinaNet-101 are single-shot detectors, while Faster RCNN-50 …

Multiple blood images of stressed and sheared cells, taken by a Lorrca Ektacytometery microscope, needed a classification for biomedical researchers to assess several treatment options for blood-related diseases. The study proposes the design of a model capable of classifying these images, with high …

This study focuses on forecasting tomato sap flow in relation to various climate and irrigation variables. The proposed study utilizes different machine learning (ML) techniques, including linear regression (LR), least absolute shrinkage and selection operator (LASSO), elastic net regression (ENR), support …