A dataset of color fundus images for the detection and classification of eye diseases.

The retina is a critical component of the eye responsible for capturing visual information, making the importance of retinal health for clear vision. Various eye diseases, such as age-related macular degeneration, diabetic retinopathy, and glaucoma, can severely impair vision and even lead to blindness if not detected and treated early. Therefore, automated systems using machine learning and computer vision techniques have shown promise in the early detection and management of these diseases, reducing the risk of vision loss.

A literature review: machine learning-based stem cell investigation.

Background And Objective: Stem cell (SC) is a crucial factor of the human organ that is significantly important for clinical solutions. However, consideration of SC in the therapeutic or disease classification process is complex in terms of accurate classification and prediction. To overcome this issue, Machine learning (ML) is the most effective technique that is frequently used in cell-based clinical applications for diagnosis, treatment, and disease identification.

Effects of behavioural change communication (BCC) on menstrual hygiene practices among urban school adolescent girls: a pilot study.

Background: Research on menstrual hygiene management practices (MHMP) has yet to be conducted among adolescent girls in Bangladesh who have gained services from the Urban Primary Health Care Project (UPHCP). This study aimed to assess the effects of behavioural change communication activities on MHMP among urban school adolescent girls.

Methods: A convenience sample of 270 adolescent girls (aged 10-19) who had no chronic diseases from 5 schools in Dhaka city was selected using a descriptive cross-sectional design from February to May 2018.

A comprehensive dragon fruit image dataset for detecting the maturity and quality grading of dragon fruit.

Dragon fruit, often referred to as pitaya, is a tropical fruit with various types, including both white-fleshed and red-fleshed varieties. Its distinctive appearance is complemented by a range of potential health advantages. These include its abundance of nutrients and antioxidants, which contribute to a robust immune system, aid in blood sugar regulation, and support the well-being of the heart, bones, and skin.

An extensive real-world in field tomato image dataset involving maturity classification and recognition of fresh and defect tomatoes.

Tomato, a fruiting plant species within the Solanaceae family, is a widely used ingredient in culinary dishes due to its sweet and acidic flavor profile, as well as its rich nutritional content. Recognized for its potential health benefits, including reducing the risk of coronary artery disease and specific types of cancer, tomatoes have become a staple in global cuisine. Traditional methods for tomato maturity assessment, harvesting, quality grading, and packaging are often labor-intensive and economically inefficient.