Self-Tracking for Distinguishing Evidence-Based Protocols in Optimizing Human Performance and Treating Chronic Illness

Self-tracking technologies used by healthy self-experimenters and chronic illness patients are relatively new but offer potential to accelerate the discovery of evidence-based protocols in the fields of human biology and medicine. Among both academic researchers and real-world practitioners in these fields there is an ever-present body of misinformation, leading to the proliferation of myth-based protocols in health-promoting lifestyles and treatment. This collection of four case studies spanning seven years’ worth of observations in a self-experimenting endurance athlete and, later, chronically ill individual, aims to bring to attention themost common incorrect assumptions regarding: nutrition, athletic performance, sleep, and treatment of hypothyroidism. We hope that, with these insights about misleading scientific conclusions, artificial intelligence researchers and anyone interested in developing technological solutions for public health purposes, will explore ways to bridge the gap between academic research and real-world practice of optimizing human biology, and rid the misinformation on bothsides.