Prediction of brain stroke

Keywords: Prediction of, Brain, Stoke

Background

Deep learning is experiencing huge popularity recently in the field of medicine. The prediction of brain stroke using ANN will help the medical fraternity as well as the patients in having a timely treatment which will avoid the loss of life to some extent. Artificial Neural Network (ANN) model will be trained with the related medical data of the patient and the trained model will analyze the new data which will predict the brain stroke. There are a few challenges in analyzing this dataset like having the limited data of the patients to train the model and to make the model study the underlying complex patterns and non-linear relationships. The ANN model for forecasting strokes requires data of the patient like gender, age, medical conditions, and any other symptoms. These will help the model to establish the patterns between the features. The challenges can be overcome by using neural networks which is a powerful algorithm which can undergo training and validation process by using the weights and biases in the among the neurons in neural networks to reduce the prediction errors.

Aim & Objectives

Aim
To Predict the Brain Stroke Data Using DL Methods
Objective
Develop a deep learning model to predict the likelihood of brain stroke using medical data.
Train the model with comprehensive health information to accurately classify stroke risk.
Evaluate model's performance to offer reliable predictions, aiding early stroke prevention using DL methods.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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