Application of Machine Learning for the Prediction of Strokes in Peru

Matta-Solis H.; Perez-Siguas R.; Matta-Solis E.; Matta-Zamudio L.; Millones-Gomez S.; Velarde-Molina J.F. · International Journal of Engineering Trends and Technology (2022) · DOI: 10.14445/22315381/ijett-v70i10p207

Resumen

- Strokes are one of the most common causes of death or disability worldwide; several proposals have been put forward to reduce these accidents. The goal of the research is to create a machine learning model, which will help us predict the probability of how likely a person is to suffer or suffer a stroke. To do this, machine learning techniques were applied, as these have evolved exponentially over the years, and a dataset of stroke patients and stroke-free patients was used to train the model. As a result, our model obtained an accuracy of 77% for patients who could suffer from this disease, after which prevention can be done and thus achieve a decrease in the mortality rate from strokes.

Instituciones: Escuela de Posgrado Newman