An Efficient Deep Learning Mechanism for the Recognition of Olive Trees in Jouf Region.

Olive trees grow all over the world in reasonably moderate and dry climates, making them fortunate and medicinal. Pesticides are required to improve crop quality and productivity. Olive trees have had important cultural and economic significance since the early pre-Roman era.

Olive Disease Classification Based on Vision Transformer and CNN Models.

It has been noted that disease detection approaches based on deep learning are becoming increasingly important in artificial intelligence-based research in the field of agriculture. Studies conducted in this area are not at the level that is desirable due to the diversity of plant species and the regional characteristics of many of these species. Although numerous researchers have studied diseases on plant leaves, it is undeniable that timely diagnosis of diseases on olive leaves remains a difficult task.

Machine Learning Approach for Autonomous Detection and Classification of COVID-19 Virus.

As people all over the world are vulnerable to be affected by the COVID-19 virus, the automatic detection of such a virus is an important concern. The paper aims to detect and classify corona virus using machine learning. To spot and identify corona virus in CT-Lung screening and Computer-Aided diagnosis (CAD) system is projected to distinguish and classifies the COVID-19.

Tuberculosis Disease Diagnosis Based on an Optimized Machine Learning Model.

Computer science plays an important role in modern dynamic health systems. Given the collaborative nature of the diagnostic process, computer technology provides important services to healthcare professionals and organizations, as well as to patients and their families, researchers, and decision-makers. Thus, any innovations that improve the diagnostic process while maintaining quality and safety are crucial to the development of the healthcare field.

Data on healthcare perceptions about system risk factors associated with patient safety from the Ministry of Health hospitals in Hail Region of Saudi Arabia.

Patient protection has become one of the key elements of the quality of health care systems in Saudi Arabia. Medical errors that threaten patient safety are mediated by several factors including system risk factors. Hence, we used a self-structured questionnaire to assess and rank the system factors according to the perceptions of nurses working in the hospitals of the ministry of health in Hail, KSA.