首页|New Research on Machine Learning from University of Bristol Summarized (Scoping review: Machine learning interventions in the management of healthcare systems)
New Research on Machine Learning from University of Bristol Summarized (Scoping review: Machine learning interventions in the management of healthcare systems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-New research on artificial intelligenc e is the subject of a new report. According to newsreporting out of the Univers ity of Bristol by NewsRx editors, research stated, "Healthcare institutions focus on improving the quality of life for end-users, with key performance indicator s like access to essentialmedicines reflecting the effectiveness of management. Effective healthcare management involves planning,organizing, and controlling institutions built on human resources, data systems, service delivery, access tomedicines, finance, and leadership."Funders for this research include Engineering And Physical Sciences Research Cou ncil.Our news correspondents obtained a quote from the research from University of Br istol: "Accordingto the World Health Organization, these elements must be balan ced for an optimal healthcare system.Big data generated from healthcare institu tions, including health records and genomic data, is crucialfor smart staffing, decision-making, risk management, and patient engagement. Properly organizing a ndanalysing this data is essential, and machine learning, a sub-field of artifi cial intelligence, can optimize theseprocesses, leading to better overall healt hcare management. This review examines the major applicationsof machine learnin g in healthcare management, the algorithms frequently used in data analysis, their limitations, and the evidence-based benefits of machine learning in healthcar e. Following PRISMAguidelines, databases such as IEEE Xplore, ScienceDirect, AC M Digital Library, and SCOPUS were searchedfor eligible articles published betw een 2011 and 2021. Articles had to be in English, peer-reviewed, andinclude rel evant keywords like healthcare, management, and machine learning. Out of 51 rele vantarticles, 6 met the inclusion criteria. Identified algorithms include topic modelling, dynamic clustering,neural networks, decision trees, and ensemble cl assifiers, applied in areas such as electronic health records,chatbots, and mul ti-disease prediction."
University of BristolCyborgsEmerging TechnologiesMachine Learning
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