A Method for the Diagnosis of Diseases That Is Based on Machine Learning: An Analysis

Sanuj Goyal; Gurpreet Kaur

Sanuj Goyal
Gurpreet Kaur

Abstract

Reliable disease detection is in high demand worldwide. Machine Learning, a form of AI, has been effective in medical diagnosis, especially. Machine learning methods have been found to diagnose both common and rare illnesses. The intricacy of many disease processes and the patient population's underlying symptoms make developing an early diagnostic tool and a successful therapy challenging. Despite these challenges, both areas have advanced. Researchers, doctors, and patients now have a tool to address some of these issues. Machine learning (ML) created this technology. This article describes how machine learning (ML) is helping diagnose a variety of diseases early. This article relies on related research. This study summarizes machine learning-based disease diagnostics (MLBDD) advances. The algorithm, data type, illness diagnosis, application, and assessment metrics were considered. This study highlights the most important findings and offers a glimpse into MLBD’s future.

Keywords: artificial neural networks, deep learning, deep neural networks, disease diagnosis, heart disease, kidney disease, machine learning

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