ABSTRACT
With a working principle similar to the human brain, deep learning algorithms handles a vast amount of data to inform an intelligent decision making. Instead of depending on manually created features or subject-matter knowledge, deep learning algorithms can discover features directly from the raw data. To produce various forms of reactions, it employs machine learning and deep learning algorithms. Deep learning algorithms have the ability to analyze medical images such as MRI, CT scans, and X-rays to diagnose anomalies and identify infections. Deep learning algorithms can evaluate enormous volumes of data to find risk factors and forecast results, enabling individualized therapy and care. Deep learning algorithms have the ability to spot anomalies and notify medical staff of potential health issues, allowing for early intervention and prevention. Based on prior interactions and the usage of Deep learning algorithms, the assistant generally offers a better user experience each time a command is given to it.
