Assessing the impact of tech-driven solutions to manage COVID-19 in Saudi Arabia: insights from health information technology professionals.

Introduction: The outbreak of the COVID-19 pandemic has disrupted the provision of healthcare services, forcing health systems, governments, and other public health stakeholders to embark on alternative means to deliver care.

Method: This scenario has fueled the adoption of digital health technologies in the healthcare industry to enhance the management of the COVID-19 pandemic. This study aimed to investigate the effect of using health information technologies (HITs) in managing the COVID-19 pandemic in Saudi Arabia from the health information technology professionals' perspectives.

Utilizing deep learning models in an intelligent spiral drawing classification system for Parkinson's disease classification.

Introduction: Parkinson's disease (PD) is a neurodegenerative illness that impairs normal human movement. The primary cause of PD is the deficiency of dopamine in the human brain. PD also leads to several other challenges, including insomnia, eating disturbances, excessive sleepiness, fluctuations in blood pressure, sexual dysfunction, and other issues.

Effectiveness of Artificial Intelligence (AI) in Clinical Decision Support Systems and Care Delivery.

This review aims to assess the effectiveness of AI-driven CDSSs on patient outcomes and clinical practices. A comprehensive search was conducted across PubMed, MEDLINE, and Scopus. Studies published from January 2018 to November 2023 were eligible for inclusion.

Utilizing deep learning models in an intelligent eye-tracking system for autism spectrum disorder diagnosis.

Timely and unbiased evaluation of Autism Spectrum Disorder (ASD) is essential for providing lasting benefits to affected individuals. However, conventional ASD assessment heavily relies on subjective criteria, lacking objectivity. Recent advancements propose the integration of modern processes, including artificial intelligence-based eye-tracking technology, for early ASD assessment.

Intelligent diagnosis system based on artificial intelligence models for predicting freezing of gait in Parkinson's disease.

Introduction: Freezing of gait (FoG) is a significant issue for those with Parkinson's disease (PD) since it is a primary contributor to falls and is linked to a poor superiority of life. The underlying apparatus is still not understood; however, it is postulated that it is associated with cognitive disorders, namely impairments in executive and visuospatial functions. During episodes of FoG, patients may experience the risk of falling, which significantly effects their quality of life.

Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study.

Background: Wearable insulin biosensors represent a novel approach that combines the benefits of real-time glucose monitoring and automated insulin delivery, potentially revolutionizing how individuals with diabetes manage their condition.

Study Purpose: To analyze the behavioral intentions of wearable insulin biosensors among diabetes patients, the factors that drive or hinder their usage, and the implications for diabetes management and healthcare outcomes.

Methods: A cross-sectional survey design was adopted in this study.

Public Awareness of Obesity as a Risk Factor for Cancer in Central Saudi Arabia: Feasibility of ChatGPT as an Educational Intervention.

Background: While the link between obesity and chronic diseases such as diabetes and cardiovascular disorders is well-documented, there is a growing body of evidence connecting obesity with an increased risk of cancer. However, public awareness of this connection remains limited.

Study Purpose: To analyze public awareness of overweight/obesity as a risk factor for cancer and analyze public perceptions on the feasibility of ChatGPT, an artificial intelligence-based conversational agent, as an educational intervention tool.