To fully realise the transformative power of data-driven services and personalised medicine, they require structured integration of digital and genomic innovations that network and account cultural, and ethical implications, explains James Henry.
Decades of research underscore the necessity of a strong commitment to successfully integrate artificial intelligence (AI) into Biological Modelling and Population Health Management.1 Society must determine its expectations for AI, including a culture of continuous improvement alongside the cultivation of metrics and fairness while ensuring privacy and security for reliable predictor and intercept classification in primary and social care reform.2 Furthermore, population management emphasises transitioning from a collaborative approach to the stewardship of data as a standard, aiming to fully realise AI’s potential in healthcare through data science themes within Human Phenotype Ontology domains.3
Globally, nations are uniting on wellbeing to leverage the transformative power of data-driven services in sustaining personalised medicine and establishing goals for the structured integration of genomics. This integration must network and consider cultural and ethical implications.4 This article builds upon the authors’ manuscript, ‘Culture Intelligent Workflow, Structure and Steps’, published in Frontiers in Artificial Intelligence.5 This paper and the current article frame Biological Modelling within a Population Health Ecosystem, where subsequent program manuscripts further segment pathology for improved global health practices.6-10
Introduction
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