QuantiModo consists of a web platform for integrating, visualizing, and analyzing Quantified self data. The purpose is to crowd-source clinical research, accelerating treatment and root cause discovery for chronic illnesses. It does this by mining the aggregated data for causal relationships. By quantifying these relationships using proprietary causal discovery algorithms, it is possible to present users with a list of factors that most influence their health outcomes. These factors can include countless variables relating to diet, medication, physical activity, sleep, and any other measurable realm of human activity. Quantifying the magnitude of these relationships helps to overcome the problem of information overload many suffers face when searching for solutions. QuantiModo is a major step to the era of personalized medicine, by overcoming the limitations of traditional research models. There are major limitations of the human mind with regard to its bandwidth for consuming new information, the disk space for storing this information, and the processing power to apply it. With infinitely scalable virtual technologies, it is now possible to overcome these limitations through applied machine learning. The human mind is not powerful enough to keep track of the countless factors that go into producing an emotional state. Quantimodo can help by synergizing, visualizing, and analyzing the cacophony data to identify correlations between specific input factors and treatments (independent variables) and mood outcomes (dependent variables). Fine-grained, personalized minimum effective dosages can be established. Degrees of drug tolerance and withdrawal symptoms can be quantified. By integrating the area under the mood curves, true cost-benefit analyses weighing therapeutic benefits against adverse effects can be performed.