On January 29-30, 2018, the NLM hosted Viral Networks: An Advanced Workshop in Digital Humanities and Medical History, bringing together scholars from various fields of medical history whose innovative research shows promise through the use of methods, tools, and data from the digital humanities. The event was supported by the National Endowment for the Humanities (NEH) through a grant to Virginia Tech, and was a collaborative outcome of NLM's long standing partnership with the NEH.

Viral Networks, Reconnected reunites three scholars who participated in the January 2018 Viral Networks workshop, offering them the opportunity to share the progress of their research and their thoughts about the future of the digital humanities and the history of medicine.

Viral Networks, Reconnected is co-sponsored by the National Endowment for the Humanities, Office of Digital Humanities.

A Network of Number Doctors: Biostatistics at the NIH Christopher J. Phillips, Assistant Professor, Department of History, Carnegie Mellon University

Between roughly 1930 and 1980, statistical analysis became a central component of clinical medicine. Long used in public health and epidemiology, biostatistical tools and concepts were increasingly deployed to answer the most basic of clinical inquiries: Is this therapy effective? How long will this patient survive? Is this substance carcinogenic? Biometricians and biostatisticians at the National Institutes of Health were central to this transformation, both establishing and promoting new techniques. In this presentation I will combine traditional historical tools with newer digital tools to argue that one important way NIH statisticians were able to effect such change was through networks of influence, including project consultation, expert review panels, and co-publication practices. By thinking of statisticians as a network constituted both inside and outside the NIH, we can better understand the rapid transformation of clinical medicine into a field where probabilities, inference tests, and meta-analyses now play decisive roles.

Networked History: Developing Quantitative Models of Qualitative Phenomena A. R. Ruis, Associate Director for Research of the Epistemic Analytics Lab, Wisconsin Center for Education Research, and Fellow of the Medical History and Bioethics Department, University of Wisconsin-Madison

Scholars in the humanities and social sciences are newly confronted with staggering amounts of source material. From digitized collections of historical records to the cyberarchives of online communities, traditional research methods are difficult if not impossible to apply when the volume of data exceeds what a human can reasonably read and evaluate. But as scholars turn to computational techniques designed for distant reading and adapt analytic approaches from other contexts, such as computational linguistics and machine learning, it raises questions about the nature of historical research and criteria by which we evaluate the quality of historical arguments. In this presentation, I explore the use of a network analytic technique, epistemic network analysis, for modeling and investigating the ontological foundations of nutrition over two centuries. Using this case study as a worked example, I examine the strengths and limitations of such an approach and the implications of outsourcing some of our analytic thinking to machines.

Naming, Networks, and Power in Histories of Medicine in Africa Sarah, Runcie, Assistant Professor of African History, University of Louisiana at Lafayette

This presentation will explore how scholars can bring together digital tools and network analysis with key questions of power in histories of medicine in Africa. It will take a particular focus on the potential for digital tools to highlight the role of Africans in biomedical practice during the colonial period.