Biomimicry and Machine Learning in the Context of Healthcare Digitization

Abstract

The healthcare industry is inundated with elder, disabled, and partial-use care issues such as falls in homes with no available aid present. This article’s thesis is that bio-support in the form of biomimetic artificial intelligence (AI) is not yet fully-exploited within the stated problem space. This article summarizes analyses conducted using Hancock’s “Knowledge-Based Expert System” (KBES) on two datasets from the popular machine learning website Kaggle. The first dataset contains various numeric, health-related data from 400 anonymized patients diagnosed with chronic kidney disease (CKD). The second contains the same kind of data, but for 569 patients diagnosed with either malignant or benign forms of breast cancer. In the last place, the potential for a “Holacratic” health analytics organization will be assessed. Said organization would be akin to Tapscott’s “Global Solutions Network” (GSN), which was defined as a digital group of public or private individuals with the following four features: Diversity in stakeholders who collectively represent at least two of the four pillars of society (government, private sector, civil society, individuals)Multinational or global presenceAt least partial digitality with respect to its communications tools and platformsProgressive goals related to the creation of public goods It will be argued that the group working on this article (known colloquially as the Sirius Project) successfully addresses both the criteria of being and need for a Holacratic GSN.