**6. Rise of artificial intelligence (AI) in healthcare: transformative future**

The sophistication of artificial intelligence (AI) in doing what humans do has increased by leaps and bounds in the last one decade. In 2019, AI is a fact today and we have seen a shift in the conversation. We are no longer answering the question what is AI? Today, the primary concern is answering the question—how can we utilize the plethora of information to replicate the human actions in a more efficient and faster way? No other sector is answering this question better than Healthcare. Artificial intelligence and computer simulations are no longer a novelty and if things progress the way they are, these may soon be the norm.

The use cases for AI in healthcare are vast and ever evolving. Just like AI has become a seminal part of our daily lives, AI is also transforming our healthcare ecosystem. When AI is applied strategically to this ecosystem, it not only has the ability to deeply impact the way healthcare is delivered but also how that the healthcare impacts the overall cost structure.

**81**

*Computer Simulation and the Practice of Oral Medicine and Radiology*

Today, AI has pushed innovation in healthcare to the next level by combining the training data sets with cognitive computing to draw new insights and correlations. This has been possible because of predictive capabilities, complex algorithms and analytics to deliver real time data that is clinically relevant, i.e., transforming

First and foremost, is to help people stay healthy and eventually reducing the frequency of patient and doctor interaction. The new health apps encourage people to live a healthy lifestyle. AI equips healthcare professionals to better understand everyday health patterns and the needs of their patients. The increased use of consumer hardware technologies such as Apple Watch and other medical devices combined with AI is used in pilot projects such as detecting early-stage heart disease. Thus, helping healthcare professionals to better detect and monitor underlying life-threatening events at early, more treatable stages. With more and more money being invested in projects like Apple Health and Common Health of Android platform, the upheavals in how we practice as diagnosticians, are going to

Recently, life threatening diseases such as cancer are being detected more accurately by AI in their early stages. Based on the study done by American Cancer Society, a large proportion of mammograms eventually result in false positives, i.e., 1 in 2 healthy women are diagnosed with cancer when they have none. Using AI in review and translation process of mammograms may help to avoid unnecessary biopsies.

**8. Simulation and requirements for artificial intelligence (AI)-aided** 

four requirements that we think, are of paramount importance for AI guiding

computer simulations, to be helpful in the field of Oral Radiology, are:

the diagnosis process easy and viable to the doctors [3].

AI has to meet several demands to be used widely in clinical practice. The major

a.*AI should improve radiologists' performance—*which means that efficacy and the accuracy of detecting the aberrancy in the scan should be picked up by the AI

b.*AI should save time—*it should save the radiologist in detecting and diagnosing a disease. One of the important factors which adds efficacy of a system for any machine is that it reduces time. If an AI system is not decreasing the time for the diagnosis process then it is not helping the radiologist at its 100% [3].

c.*AI must be seamlessly integrated into the workflow—*The AI system should be a part of the diagnosis process without being a process in itself. It should make

d.*AI should not impose liability concerns—*The AI system used should be HIPAA compliant system and there should have a foolproof close system to prevent

Most AI systems, and therefore computer simulations used in diagnostics that are based on these, today do not meet all requirements, and this is why most applications described in the rapidly growing body of scientific literature on CAD

*DOI: http://dx.doi.org/10.5772/intechopen.90082*

**7. Innovation curve**

healthcare in new ways.

be tectonic.

**systems**

system [3].

any data breach [3].

are not widely used in clinical practice.
