Bio

Sylvia Hobbs is an epidemiologist with a special interest in philosophical issues of measurement and how the logic of measurement at the atomic level translates into statements about biological complexity at the macroscopic level. She is fascinated by variants of Bell’s theorem and how both science and poetry unravel the functional dependence of higher macroscopic order on lower order unobservable attributes. While in grad school, she studied the philosophy of physics and biology with distinguished Bell’s theorem physicist Abner Shimony. Her favorite Biblical passage is Second Corinthians 4:18: “So we fix our eyes not on what is seen, but on what is unseen, since what is seen is temporary, but what is unseen is eternal.” She has a bachelor of arts degree in French literature from Oberlin College and a masters in epidemiology and biostatistics from Boston University. For the past decade, she has worked as a government research director focusing on exploring geographic dynamics around health outcomes using multilevel models and GIS. She enjoys performance poetry and on occasion busts a rhyme on local cable television and at area nightclubs.

Project: Towards Visualizing Mortality Risk Based on Current Taxonomies for Anatomic Damage

The ability of technology such as diagnostic CT scans to generate digital geometry 3D images of anatomic level damage to the human body on a single axis of rotation has come a long way since French physician Jacques Bertillon introduced the Classification of the Causes of Death at a 1893 congress of the International Statistic Institute. CT scans are now routine, and Bertillon’s original anatomic nomenclature has undergone 10 revisions, becoming the World Health Organization’s International Statistical Classification of diseases (ICD-10), the world’s most widely used coding scheme for mortality statistics. Despite technological and coding innovations, two major scientific problems persist in the area of quantifying anatomic damage. They include the need to statistically summarize mortality risks associated with multiple injuries where the most severe injuries are hierarchically categorized and the need to describe anatomic injury severity so that case-mixed groupings can be considered when quantifying mortality risks. While cellular automata and combinatorics have been successfully deployed to interpret and hierarchicize the topology of complex variation in control systems at the physiologic level (e.g. brain nerve cell activity, cardiac oscillations, respiration, and hematopoiesis), no standard tool exists at the anatomic level to visualize mortality risks associated with severity taxonomies. This project explores the tenability of doing so.

Favorite Four-Color Totalistic Cellular Automaton

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