Chapter 11 - Combining Predictive Analytics and Artificial Intelligence With Human Intelligence in IoT-Based Image-Guided Surgery

Abstract

When analyzing the history of medical surgery, we can see that humans have developed and refined instruments for surgical procedures. Evolution in medical advancements is on a par with that observed in the disease-causing agents and viruses. Starting from a medical era during which invasive surgeries were performed without anesthesia, the need for painless, safe, hygienic, and successful surgeries has led to the modern era of surgery, which has a relatively small mortality rate. The practical use of minimally invasive approaches that result in fewer wound-related complications, quick organ function return, and shorter hospitalizations has led to higher acceptance of image-guided surgical procedures. In our proposed system, we present an IoT-based surgical model that involves a virtual reality-based (VR-based) user interface, predictive analytics that predict the “what-ifs” for an activity to be performed during the surgery based on the data collected during similar previous surgeries, and artificial intelligence that learns from the same dataset used by predictive analytics to assist surgeons during the surgery. Virtual reality refers to an environment artificially created by the support of computer software. When humans access such an environment, they believe that they are actually there in the artificially created environment. Headsets and other navigators can be used along with the VR set-up in order to provide a more immersive environment. The experience obtained through the power of VR is no less than the actual reality. For a more immersive experience, the Oculus Rift VR system is to be used as part of the proposed model. The VR system is to be connected to the SAP IoT interface of the SAP Cloud system. Predictive analytics is one of the latest software paradigms that enables analysis of large datasets and prediction of future outcomes and behavior. It involves building a predictive analytics model by using big data and IoT sensors to uncover hidden risks, explore unforeseen opportunities, and reach a better understanding. In our proposed model, SAP predictive analytics is to be deployed to build a surgical predictive model that could provide real-time predictions during surgery based on the data collected during previous surgeries. Artificial intelligence is a computing paradigm used to create systems that automate intelligent processes. AI can be used for learning, problem solving, and decision-making processes and can work with a speed and precision that humans are able to achieve only with great effort. AI is to be deployed in our proposed surgical model to minimize the surgeons’ efforts in navigating the noninvasive surgical equipment and the camera. Often there is a difference between the intention with which a surgeon navigates and the actual navigation which happens internally during the surgery. The surgeon has to put in more effort to overcome this mismatch. In order to address this issue, formulating AI in the surgical internal device navigation could result in reduced manual effort by the surgeon, which in turn would help him in concentrating on comparatively more important surgical thoughts and activities. The SAP Leonardo Machine Learning feature is to be deployed in the proposed model.