Sabrina Yu, Paul Aiello, Aby Mathews Maluvelil, Obed Ehoneah, Vishva Shah, Samuel Numor
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引用次数: 0

摘要

移动医疗(mHealth)应用的快速发展凸显了对强大的评估平台的迫切需求,以确保质量、功效和利益相关者的一致性。本文介绍了一种基于证据的定量框架,通过动态属性加权和多标准决策分析来弥补这些不足。该平台整合了 CRITIC-TOPSIS 和人工智能驱动的属性优先级排序等方法,并通过系统回顾和专家分析进行了验证。初步评估表明,该平台具有针对各种移动医疗应用和利益相关者需求提出可行见解的潜力。未来的工作包括详细的文献综述、平台开发和实际用例部署,以完善其适用性和影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing an Evidence-Based Evaluation Framework for mHealth Applications.

The rapid growth of mobile health (mHealth) applications underscores the pressing need for robust evaluation platforms that ensure quality, efficacy, and stakeholder alignment. This paper introduces a quantitative, evidence-based framework that addresses these gaps through dynamic attribute weighting and multi-criteria decision analysis. The platform integrates methodologies such as CRITIC-TOPSIS and AI-driven attribute prioritization, validated through systematic reviews and expert analyses. Preliminary evaluations demonstrate potential for generating actionable insights tailored to diverse mHealth applications and stakeholder needs. Future work includes detailed literature reviews, platform development and real-life use case deployment to refine its applicability and impact.

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