Medical diagnosis is an important and also delicate and time involving task that needs to be carried out in order to accurately identify a disease a patient might be suffering from. Due to the inaccurate diagnosis given to patients which could result in a wrong prescription that may lead into unwelcome consequences therefore to help in this direction an automated system is developed which is able to generate the association rules among different symptoms which will also assist the medical personnel in diagnosing patient’s diseases accurately. In actualizing this aim, an analysis technique in data mining which is Market Basket Analysis using bitmap representation of Transaction table is adopted in revealing the association rule among the symptoms and diseases given a support and confidence level. The rules generated are compared with a doctor’s prescription to determine its relevance in healthcare, the irrelevant ones are then filtered out to ascertain the ones which are acceptable for diagnosis of the various diseases.