IQ INTELLIGENCE is a fast-growing professional training provider that is offering classroom and online training in over 20 most sought-after tools and technologies. We have a learner base in Canada and USA. We help organizations maximize the impact of our training by customizing the curriculum to make sure we cover the topics relevant to your group. We help fast learn the skills within days where it you can start applying the new tools as soon as possible.

IQ INTELLIGENCE offers a comprehensive Artificial Intelligence Master's course to become a certified Artificial Intelligence in Medicine Engineer. This training will help you learn various aspects of Medical artificial intelligence (AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. AI has the capability of detecting meaningful relationships in a data set and has been widely used in many clinical situations to diagnose, treat, and predict the results. The purpose of this special course is to demonstrate the potential of several intelligent approaches in medical informatics technologies and applications. Submissions for this special course should be original work that deals in some manner with topics relevant to medical artificial intelligence, expert systems, data mining, machine learning, and image processing. The main focus of this course will be on the proposal of techniques for medical artificial intelligence, expert systems, data mining, machine learning, and image processing which could be built on top of them.

Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more detail the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with a discussion about pioneer AI systems, such as IBM Watson, and hurdles for the real-life deployment of AI. Potential Contents include but are not limited to the following:

•  Artificial intelligence techniques in medicine
•  Data mining and knowledge discovery in medicine
•  Medical expert systems
•  Machine learning-based medical systems
•  Medical signal and image processing techniques