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Background: Digital health innovations provide an opportunity to improve access to care, information, and quality of care during the perinatal period, a critical period of health for mothers and infants. However, research to develop perinatal digital health solutions needs to be informed by actual patient and health system needs in order to optimize implementation, adoption, and sustainability.

Objective: Our aim was to co-design a research agenda with defined research priorities that reflected health system realities and patient needs.

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Background: Assisted partner services (APSs; sometimes called index testing) are now being brought to scale as a high-yield HIV testing strategy in many nations. However, the success of APSs is often hampered by low levels of partner elicitation. The Computer-Assisted Self-Interview (CASI)-Plus study sought to develop and test a mobile health (mHealth) tool to increase the elicitation of sexual and needle-sharing partners among persons with newly diagnosed HIV.

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Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.

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Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition emerging in early childhood, characterized by core features such as sociocommunicative deficits and repetitive, rigid behaviors, interests, and activities. In addition to these, disruptive behaviors (DB), including aggression, self-injury, and severe tantrums, are frequently observed in pediatric patients with ASD. The atypical antipsychotics risperidone and aripiprazole, currently the only Food and Drug Administration-approved treatments for severe DB in patients with ASD, often encounter therapeutic failure or intolerance.

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Background: There has been a rise in the popularity of ChatGPT and other chat-based artificial intelligence (AI) apps in medical education. Despite data being available from other parts of the world, there is a significant lack of information on this topic in medical education and research, particularly in Saudi Arabia.

Objective: The primary objective of the study was to examine the familiarity, usage patterns, and attitudes of Alfaisal University medical students toward ChatGPT and other chat-based AI apps in medical education.

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