Users' experience with health-related content on YouTube: an exploratory study.

Background: This study focuses on health-related content (HRC) on YouTube and addresses the issue of misinformation on this platform. While previous research centered on content evaluations by experts, this study takes a user-centered approach and aims to explore users' experiences with and perceptions of HRC videos and to establish links between these perceptions and some socio-demographic characteristics including age, gender, profession, and educational level.

Methods: A quantitative research design was used in the study.

Drone-Person Tracking in Uniform Appearance Crowd: A New Dataset.

Drone-person tracking in uniform appearance crowds poses unique challenges due to the difficulty in distinguishing individuals with similar attire and multi-scale variations. To address this issue and facilitate the development of effective tracking algorithms, we present a novel dataset named D-PTUAC (Drone-Person Tracking in Uniform Appearance Crowd). The dataset comprises 138 sequences comprising over 121 K frames, each manually annotated with bounding boxes and attributes.

Is YouTube a reliable source of health-related information? A systematic review.

Background: YouTube is a valuable source of health-related educational material which can have a profound impact on people's behaviors and decisions. However, YouTube contains a wide variety of unverified content that may promote unhealthy behaviors and activities. We aim in this systematic review to provide insight into the published literature concerning the quality of health information and educational videos found on YouTube.