PREDICTING CANCER AND HEART DISEASE AT EARLY STAGES USING MACHINE LEARNING

Abstract

People today suffer from a variety of diseases as a result of their living habits and their surroundings. As a result, predicting sickness at an early stage becomes a critical responsibility. Machine learning has been demonstrated to be useful in assisting with decision-making and prediction from enormous amounts of data generated by the health sector. As a result, machine learning's use in medical diagnostics is rapidly rising. Heart disease is one of the leading causes of death in the modern world. Predicting and detecting cardiac disease has always been a difficult issue for medical professionals. To treat cardiac disorders, hospitals and other clinics are offering costly medicines and operations. As a result, anticipating cardiac disease in its early stages will be beneficial to people all over the world, allowing them to take the essential steps before it becomes serious. Cancer has been described as a diverse illness with numerous subgroups. Early detection and prognosis of a cancer type has become a necessity in cancer research since it can help with patient clinical treatment. The health industry nowadays plays a key part in curing patient’s problems, thus this is also a way for the health sector to enlighten users. It is useful for the user if he or she does not want to go to the hospital or any other clinic, because by simply entering the symptoms and other relevant information, the user can learn about the disease they are suffering from. The health industry can also benefit from this system by simply asking the user for symptoms and entering them into the system, and in a matter of seconds, they can tell the exact and, to a degree, accurate diseases.