Authors :
Wijesinghe H T; Senevirathne W S M S L; Shashika Lokuliyana; Hansika Mahaadikara
Volume/Issue :
Volume 7 - 2022, Issue 10 - October
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3tU835R
DOI :
https://doi.org/10.5281/zenodo.7353050
Abstract :
Cardiovascular Diseases (CVD) is a group of
dis- eases that affect a person’s heart and blood vessels.
Compared to other diseases, this is one of the leading
causes of mortality worldwide. Early detection is critical in
many hearts related illnesses to reduce the number of
deaths. Loss of life could arise from improperly analyzing
the precise symptoms of risky diseases. A system that uses
optimal algorithms to analyze human vital patterns and
anticipate serious diseases is created. Predicting the
probability of cardio diseases using human vital patterns
is highlighted here. This project offers a prediction model
to determine if a patient has a heart illness or not based on
symptoms given in a web-form, as well as to raise
awareness about heart disease and provide some helpful
heart disease suggestions. Both supervised and
unsupervised machine learning algorithms are used in this
system. The web page is the main method of
communication in this system. After entering the necessary
information into the system, the system will notify the
user whether he/she has a cardiac problem. Furthermore,
if the data (blood pressure, heart rate) surpass the
threshold limits, an emergency alert is sent to hospitals and
ambulatory care facilities.
Keywords :
Cardio, Supervised, Unsupervised.
Cardiovascular Diseases (CVD) is a group of
dis- eases that affect a person’s heart and blood vessels.
Compared to other diseases, this is one of the leading
causes of mortality worldwide. Early detection is critical in
many hearts related illnesses to reduce the number of
deaths. Loss of life could arise from improperly analyzing
the precise symptoms of risky diseases. A system that uses
optimal algorithms to analyze human vital patterns and
anticipate serious diseases is created. Predicting the
probability of cardio diseases using human vital patterns
is highlighted here. This project offers a prediction model
to determine if a patient has a heart illness or not based on
symptoms given in a web-form, as well as to raise
awareness about heart disease and provide some helpful
heart disease suggestions. Both supervised and
unsupervised machine learning algorithms are used in this
system. The web page is the main method of
communication in this system. After entering the necessary
information into the system, the system will notify the
user whether he/she has a cardiac problem. Furthermore,
if the data (blood pressure, heart rate) surpass the
threshold limits, an emergency alert is sent to hospitals and
ambulatory care facilities.
Keywords :
Cardio, Supervised, Unsupervised.
