While we wait for Watson to finish medical school and make a web app, Wolfram|Alpha has announced a recent addition of more medical tools to its already impressive database. The Wolfram|Alpha team accomplished this by applying their existing data retrieval and presentation methods to loads of CDC data. A search for a chief complaint such as chest pain will bring up epidemiology (for the US since the data is from CDC), incidence, and a differential diagnosis. Basically, Wolfram|Alpha is now the world’s fastest 2nd yr medical student on morning rounds.
Wolfram|Alpha also supplies the conditional probabilities for which select sub-populations are affected by a queried symptom, as well as the percentage of patients with the symptom who utilized specific healthcare payment methods. Besides single symptoms, multiple symptoms can also be searched through Wolfram|Alpha. For example, after entering “anxiety and depression”, the data that is returned reflect those patients who reported or were diagnosed with depression and anxiety during a healthcare provider visit in a given year. Data can also be queried by attributes that include age, gender, and weight. For example, users can add an age to the previous example (e.g. “anxiety and depression age 37”) and get a tailored output specific to patients between 30 and 40 years old.