Paper Title
Data Science and Business Analytics Models and Applications in Mental Health
Article Identifiers
Registration ID: IJNRD_200570
Published ID: IJNRD2307007
: http://doi.one/10.1729/Journal.35084
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Keywords
mobile computing; cloud computing; Fast Healthcare Interoperability Resources; artificial intelligence; healthcare delivery; clinical decision support; predictive modeling
Abstract
The rapid advancements in mobile computing, cloud computing, and artificial intelligence (AI) have opened new possibilities for transforming healthcare delivery. The significant benefits of leveraging the enhanced capabilities of these technologies and their emerging trends, such as "mobile first" healthcare, the Internet of Things (IoT), and IoT-enabled assistive technologies, are expected to impact healthcare delivery systems positively. The power of mobile computing, cloud computing, and AI in healthcare delivery is only beginning to be realized. Mobile healthcare applications, such as electronic health records (EHRs) that allow users to access their information from any location via mobile devices have already provided several tangible benefits. The applications have significantly improved patient safety through real-time data sharing and instant medical records and metrics access. This manuscript explores the integration of these technologies in the healthcare industry, with a specific focus on the combination of Fast Healthcare Interoperability Resources (FHIR) and AI. Leveraging the power of FHIR and AI, healthcare providers can enhance clinical decision support, improve predictive modeling, and ultimately enhance patient outcomes. This manuscript discusses the benefits, challenges, and considerations associated with integrating mobile computing, cloud computing, and AI in healthcare and highlights the potential for revolutionizing healthcare delivery. The results section presents the potential benefits of integrating mobile computing, cloud computing, and AI in healthcare. It discusses how AI-powered analytics tools can process and analyze structured FHIR data, discovering new correlations, risk factors, and treatment options.
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How To Cite (APA)
LEELAKUMARRAJA LEKKALA (July-2023). Data Science and Business Analytics Models and Applications in Mental Health. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(7), a47-a52. http://doi.one/10.1729/Journal.35084
Issue
Volume 8 Issue 7, July-2023
Pages : a47-a52
Other Publication Details
Paper Reg. ID: IJNRD_200570
Published Paper Id: IJNRD2307007
Research Area: Health ScienceÂ
Author Type: Foreign Author
Country: Louisville, KY, United States
Published Paper PDF: https://ijnrd.org/papers/IJNRD2307007.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307007
Crossref DOI: http://doi.one/10.1729/Journal.35084
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