IMPLEMENTATION VIDEO FOR DIAGNOSIS OF CHRONIC LIVER DISEASE BY USING GRADIENT ALGORITHM

By first gathering a dataset of patient data and liver disease diagnoses, a supervised machine learning model for the diagnosis of chronic liver disease using the gradient algorithm may be constructed. The dataset can then be divided into training and testing sets, and an appropriate algorithm—such as logistic regression or random forest—can be trained using the gradient method on the training data. Utilising the testing data, the model’s performance can be assessed, and any corrections required to increase its accuracy can be made. Last but not least, the trained model can be utilised to predict outcomes based on fresh patient data to help with chronic liver disease diagnosis.

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