Artificial Neural Networks in Healthcare: A Systematic Review

Abstract

As one of the paramount technologies currently machine learning is being used to reshape the healthcare sector. The objective here is to gain knowledge about machine learning and specifically neural networks and their present applications in healthcare, also to understand the technological and social challenges. Various machine learning techniques are being used in healthcare as predictive models as they achieve high accuracy results at great speeds, and they have applications in nearly all departments of a hospital. Neural networks and predictive scores are the most used techniques as they can be used to find results which are almost impossible for humans to predict like mortality rate etc. Most of the data used for training these models must be preprocessed as it may range from electronic health records to medical images like MRI, CT Scans etc. Image analysis using convolutional neural networks new discoveries are being made, while broadening the understanding of the previously known theory. There are several challenges faced in terms of data security and data preprocessing and data availability.

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