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Background: Most maternal deaths are preventable by accessing essential maternity healthcare services. However, maternal mortality rates remain high in Ethiopia partly due to only a few women using a complete Continuum of Maternal Healthcare Services (CMHS). This study aims to assess trends and contributors for complete CMHS utilization in Ethiopia.

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Background: Birth-related mortality is significantly increased by home births without skilled medical assistance during delivery, presenting a major risk to the public's health. The objective of this study is to predict home delivery and identify the determinants using machine learning algorithm in sub-Saharan African.

Methods: This study used design science approaches.

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Immersive journalism is an innovative storytelling approach that aims to enable the audience to experience the event or situation in the news using virtual reality, unlike traditional news narration. In this study, the literature related to the subject was searched using the keywords Immersive Journalism, 360-Degree Video, Narrative journalism, Newsgame, VR Storytelling through the Web of Science database and a data set was created from 955 publications between 1999 and 2023. No filter was applied to the studies in the data set of the study and articles, books, and early access publications as well as book chapters, editorial materials or conference proceedings in the Web of Science database were included in the study.

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Although there are studies on TV viewing and the health status of elderly, they do not present direct associations with specific variables. The aim of this study was to determine correlations between TV viewing variables and elderly health variables in older adults living alone. Data were collected from 50 elderly individuals with an average age of 82.

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A Neurosurgical Instrument Segmentation Approach to Assess Microsurgical Movements.

Stud Health Technol Inform

November 2024

Laboratory of Biomedical Informatics and Artificial Intelligence, cDepartment of Neurosurgery, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.

The ability to recognize anatomical landmarks, microsurgical instruments, and complex scenes and events in a surgical wound using computer vision presents new opportunities for studying microsurgery effectiveness. In this study, we aimed to develop an artificial intelligence-based solution for detecting, segmenting, and tracking microinstruments using a neurosurgical microscope. We have developed a technique to process videos from microscope camera, which involves creating a segmentation mask for the instrument and subsequently tracking it.

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