The Evolution of Artificial Intelligence Innovations in the Medical Field with Regard to their Practical and Business Applications

As stated by the Abstract, "This paper, as a whole, attempts to give an overall high-level view of the working “mechanics” of artificial intelligence-driven innovations serving practical uses in the medical field. In order to understand the market and such a system’s potential business applications, I attempt to illustrate a general history on the early algorithms that our current technology can be sourced to. From here, we examine the evolution in the technology with regards to its common uses in the field and increasingly complex methodology as processors gained more computational power. With our understanding of how the current position of such technology has come to be, we will then begin to examine more modern applications utilizing machine-learning and deep learning algorithms integrated into expert-driven systems. Once we understand the approximate current capacity of the models utilized in the medical industry, we turn to view the angle from a business perspective. In this, we examine what struggles an individual entering the market with such a technology would face and the implications that come with integrating such a model into one’s business. Following this - and considering the landscape of the market - I propose that the future of the medical field (as it’s currently being entered by technology-giants), is likely dependent upon the overall quality of their models over an extended period of time as they are - too - subject to the various biases and pitfalls that we will discuss."