Data mining technique involves extracting or mining large volume of information for KDD - knowledge discovery database. The approach of Machine learning permits the program to examine statistics, comprehend correlations and gain insights for problem solving to improve facts and predictions. In the clinical field the technique of data mining holds very significant. There are heavy volumes of patient's records in the medical enterprise, majority of which are not used effectively. In order to cure various critical or non-critical diseases the approach of data mining proves to be essential also they aid in making medical conclusions for treating various diseases. As mentioned before, the healthcare organization assembles massive lot of medical data which generally remains un-mined, resultant the hidden information remains unexplored for valuable decision making. The information if mined and discovered can prove to be beneficial for the healthcare officials for the betterment of the hospital. Many prior experiments are carried out in order to evaluate the performance but the results reveal low accuracy and unsatisfied performance. The existing paper recommends HUSP- High Utility Sequence Pattern algorithm which helps in detecting disease that affects the maximum and is most weighted, thereby highlights it in the topmost list for the benefit of the healthcare industry. Following are the levels in the recommended technique: data collection, data pre-processing, feature selection, clustering and classification in order to detect highest weighted diseases. The paper primarily targets to identify and place the most weighted disease in topmost list for the benefit of the healthcare sector. This source of data is mined/extracted effectively to draw out valuable patterns/relations. The process of sequential pattern mining is basically performed on the basis of traditional process of item-set mining, the reason being that the later approach can be generalized by interpreting the former approach. The mining algorithm of High Utility Sequence Pattern (HUSP) is an integral part of the machine learning approach. The study conducted reveals that the classification procedure yields in high accuracy.