Medical assistant using artificial intelligence
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Date
2021
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Publisher
UMT, Lahore
Abstract
Nowadays, Healthcare facilities are supposed to be critical, and it’s a basic need in human life. Data related to healthcare is enormous in the biomedical community, which can help predict diseases in early stages and detect them with more accuracy. Artificial Intelligence plays a vital role in almost every field where data is involved, primarily in the medical field. Machine Learning algorithms are producing accurate results for many different kinds of data in the medical field. It is used to predict diseases, save many lives by early diagnosis or prevention of dangerous diseases caused due to severe stages of illness just because of untimely detection. Our research is based on improving healthcare facilities in societies and backward areas. It will ideally impact the community in terms of better diagnosis of the treatment and availability 24/7. Using Artificial Intelligence as Machine Learning Algorithms to make such a system that will diagnose patients' diseases by interacting with them in a way that they can get the feeling of being treated by a real doctor. Using Artificial Intelligence in the Field of Medical is an excellent initiative towards the foresight of better health care facilities. As the population increases, the need for healthcare facilities is also growing, especially in remote areas. However, healthcare facilities are very vulnerable and need much improvement. Highly qualified doctors with good experience and excellent records in their fields. They are not easily accessible by everyone due to their busy schedules and higher consultation fees that everyone cannot afford, too, in this inflation era. In this research, MEDICAL ASSISTANT using Artificial Intelligence is proposed to predict diseases and Xrays of knee and Chest. Thus, the user/patient will be able to diagnose diseases without visiting the actual Doctor. Models' accuracy is analyzed in terms of disease prediction on training and test data. We have used different models of machine learning.