"Democratizing" artificial intelligence in medicine and healthcare: Mapping the uses of an elusive term.

"Democratizing" artificial intelligence (AI) in medicine and healthcare is a vague term that encompasses various meanings, issues, and visions. This article maps the ways this term is used in discourses on AI in medicine and healthcare and uses this map for a normative reflection on how to direct AI in medicine and healthcare towards desirable futures. We searched peer-reviewed articles from Scopus, Google Scholar, and PubMed along with grey literature using search terms "democrat*", "artificial intelligence" and "machine learning".

Rethinking Human Embryo Research Policies.

It now seems technically feasible to culture human embryos beyond the "fourteen-day limit," which has the potential to increase scientific understanding of human development and perhaps improve infertility treatments. The fourteen-day limit was adopted as a compromise but subsequently has been considered an ethical line. Does it remain relevant in light of technological advances permitting embryo maturation beyond it? Should it be changed and, if so, how and why? What justifications would be necessary to expand the limit, particularly given that doing so would violate some people's moral commitments regarding human embryos? Robust stakeholder engagement preceded adoption of the fourteen-day limit and should arguably be part of efforts to reassess it.

"Think positively": Parkinson's disease, biomedicine, and hope in contemporary Germany.

Narratives of hope shape contemporary engagements with Parkinson's disease. On the one hand, a "biomedical narrative of hope" promises that biomedical research will help to transform this treatable but incurable disease into a curable one in the future. On the other hand, a more individual "illness narrative of hope" encourages patients to influence the course of Parkinson's disease by practicing self-care and positive thinking.

Biomarkers and their consequences for the biomedical profession: a social science perspective.

Although biomarkers are not altogether new, they are gaining a new life in our postgenomic present. This article takes this as a good reason to explore biomarkers in depth and to speculate about the consequences that biomarkers might engender in clinical practices. First, the article ventures into an endeavor of ordering the dynamic field of biomarkers, suggesting a possible classification of biomarkers, and then argues that we are currently witnessing a 'biomarkerization' of health and disease - defined as an ongoing future-oriented process that seeks to solve biomedical as well as public health problems through investments into biomarker research at the present time.