Because of enormous information progress in biomedical and medical care networks, exact investigation of clinical information helps early illness acknowledgment, patient care, and community services. When the nature of clinical information is deficient, the accuracy of the study is diminished. Additionally, various areas show special appearances of certain regional illnesses, which may be debilitating the expectation of infection episodes. The proposed framework gives ML Algorithm to the viable forecast of various sickness events in disease subsequent social orders. It try the regional chronic illness of cerebral infarction. Utilizing organized and unstructured information from the emergency clinic uses the Support Vector Machine algorithm and Map Reduce algorithm. Apparently, in the space of sizeable clinical information investigation, none of the current work focused on both data types information types. Contrasted with a few average estimate algorithms, the computation precision of our proposed calculation comes to 94.8% with an assembly speed. © 2023 Elsevier B.V., All rights reserved.