Özet:
The likelihood of contracting a disease rises with the size of the human
population. Globally, there are numerous ailments, and one of the main issues facing
Healthcare systems now lack the required technology to detect illness in patients.
Cardiovascular disease, or CVD, is one such illness. Any cardiovascular, vascular, or
blood vessel ailment is referred to. More people globally die from CVDs than from
the WHO. More so in low- and middle-income nations. When ill, it can be quite
difficult for any other cause, according for persons who live alone to contact the
hospital. As a result, we created a simulation that is capable of when A sick patient
notifies the hospital in writing. a simulation that is capable of. Currently, the
simulation merely detects and informs the hospital about patients with cardiovascular
disease. We chose to focus on heart disease detection because it's one of the worst
diseases and there's a significant chance that people may pass away from it. It is a
classification problem to determine if a patient has heart disease or not. Age, blood
sugar, cholesterol, and many other factors are considered, and the output is then
provided based on the input.
We leverage both traditional machine learning and state-of-the-art deep
learning techniques. The machine learning techniques include a support vector
machine (SVM) with Artificial Neural Network (ANN ) , logistic Regression , and
