Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries

Abstract

Digital Pathology (DP) and Artificial Intelligence (AI) can be useful in low- and middle-income countries; however, many challenges exist. The United Nations developed <i>sustainable development goals</i> that aim to overcome some of these challenges. The <i>sustainable development goals</i> have not been applied to DP/AI applications in low- to middle income countries. We established a framework to align the 17 <i>sustainable development goals</i> with a 27-indicator <i>list</i> for low- and middle-income countries (World Bank/WHO) and a list of 21 <i>essential elements</i> for DP/AI. After categorization into three domains (<i>human factors</i>, IT/<i>electronics, and materials + reagents</i>), we permutated these layers into 153 concatenated statements for prioritization on a four-tiered scale. The two authors tested the subjective ranking framework and endpoints included ranked sum scores and visualization across the three layers. The authors assigned 364 points with 1.1-1.3 points per statement. We noted the prioritization of human factors (43%) at the <i>indicator</i> layer whereas IT/electronic (36%) and human factors (35%) scored highest at the <i>essential elements</i> layer. The authors considered goal 9 (industry, innovation, and infrastructure; average points 2.33; sum 42), goal 4 (quality education; 2.17; 39), and goal 8 (decent work and economic growth; 2.11; 38) most relevant; intra-/inter-rater variability assessment after a 3-month-washout period confirmed these findings. The established framework allows individual stakeholders to capture the relative importance of sustainable development goals for overcoming limitations to a specific problem. The framework can be used to raise awareness and help identify synergies between large-scale global objectives and solutions in resource-limited settings.

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