Team: 83
School: Taos High
Area of Science: Medical Science
Proposal: Skylar Spriggs, Cyrus O’hern,
Sawyer Solfest, Ryan Cox,
Henry Tosta
The Problem
In communities there are a large amount of misdiagnosis in the local medical practices.Misdiagnosis is a false diagnosis of a disease, illness or injury. Misdiagnosis occurs from a lack of shared information and research.This could be fixed via a program that analyzes symptoms to find a possible ailment.
Importance and Results
Ten to twenty percent of ailments are misdiagnosed which leads to wasted time and occasional worsened conditions. We are planning on having the program compair given symptoms to data sets and then sort them into categories of: almost certain, plausible, possible and impossible. Our results should show a saving of time while diagnosing and a more factual approach to studying possible ailments.
Methods
We intend to research one disease at a time and collect symptoms. We will code the possible ailments and what symptoms correspond with them by creating lists of symptoms connected to the ailment. For example a patient will have 5 symptoms. Using the lists associated with diseases we find that 1 symptom belongs to Disease A, 3 symptoms belong to Disease B, and 2 symptoms belong to Disease C. It will then be determined that Disease B is most likely the ailment and ask if there are other symptoms corresponding to the chosen ailment. Depending on the answers the system will determine if it needs to ask about a second possible ailment, or tell the person to see a doctor for proper diagnoses.
Team Members:
James Ryan Cox
Skylar Spriggs
Henry Tosta
Sawyer Solfest
Cyrus O'Hern