The Atlas of Artificial Illness is a physician created experimental NFT project exploring the non-human depiction of human disease - as viewed from the lens of machine learning (ML) and artificial illness (AI).
AI/ML algorithms are beginning to revolutionize modern medical practice. These modalities represent a powerful diagnostic tool for physicians that can elucidate patterns of disease with staggering accuracy, particularly with image analysis. Images of patient pathology can be presented to AI/ML systems, returning accurate diagnoses validated by physicians.
What about attempting the opposite? What is the image produced by AI/ML when a diagnosis is used as the input for an algorithm? What is the non-human visual expression of human disease, ranging from psychiatric conditions to musculoskeletal disorders?
Each token in the Atlas was produced in a systematic fashion. An image prompt was created based on a singular pathology/illness including the diagnosis, cardinal patient symptoms, corresponding ICD-10 code if applicable, and any notable data from the medical literature
20 images were produced from the initial prompt. A number generator was then used to select one image RANDOMLY. This image was then re-rolled at least 8 times until a satisfactory version was reached.
Volume 1 of the Atlas covers 100 of the most common phobias, which can be defined as an uncontrollable, irrational, and persistent fear of objects, situations, or activity. Approximately 12.5% of adults in the United States experience a specific phobia at some point in their lives (https://www.nimh.nih.gov/health/statistics/specific-phobia#part_2635). Phobias can be crippling conditions that significantly impair function - despite the fact that patients may recognize that the fear is irrational.
Holding a token from Volume 1: Phobia serves as a mint pass for all future Atlas projects
Volume 1: Phobia
Volume 2: General Pathology
Volume 3: TBD
20% of all project earnings will be donated to the National Institute on Deafness and Other Communication Disorders (NIDCD)