Abstract:
"The healthcare industry faces persistent challenges in accurately diagnosing critical health
conditions like cardiovascular diseases and brain tumors, despite remarkable technological
advancements. Accurate and timely diagnoses are crucial, directly impacting patient outcomes
and healthcare costs. Patients often endure a protracted and expensive journey of tests and
consultations in current healthcare systems, while resource constraints burden medical
professionals, leading to delayed diagnoses. The patients may struggle to buy or find the exact
medicine prescribed by doctors. Even though there are multiple drugs with same attributes
under different names, Current healthcare platforms have not been successful at suggesting
alternative medicine efficiently.
To address these issues and improve healthcare system efficiency, this research proposal
presents a comprehensive web application that seamlessly integrates multiple machine
learning models. This application aims to accurately detect critical health conditions
(cardiovascular diseases and brain tumors) and provide intelligent recommendations for
alternative medications, enhancing accessibility and efficiency for both patients and
healthcare providers."
