"Remote patient monitoring is essentially going to put a rocket launcher on telemedicine," says Waqaas Al-Siddiq, due to years of experimentation in healthcare technology with Artificial Intelligence (AI) and the lowering of costs. He credits the lowered cost for chips and connectivity, along with the proliferation of the Internet of Things (IoT), with creating a cross-pollination process – where technological advances in one area drive progress in another by clearing barriers to accessible, intelligent medicine. Al-Siddiq is the CEO of Biotricity, a remote patient monitoring company, and as such, is uniquely qualified to weigh in on emerging trends in healthcare and AI technology. Biotricity was created to fill a growing need for remote, proactive health monitoring. The company's real-time, high-precision mobile telemetry solution enhances a physician's ability to monitor a patient's condition while enabling the patient to take an active role in managing their condition.

Deep learning's pre-eminence to the enterprise today is significant for two reasons. It represents the ultimate expression of machine learning's advanced capabilities and, as such, has become virtually synonymous with artificial intelligence because of its progressive learning prowess. Deep learning is at the core of the most intricate AI capabilities including speech recognition, image and video recognition, speech generation and aspects of robotics. In considering the massive influx of unstructured data besieging enterprises such as healthcare organizations, the ascending interest in AI, and the pivotal context with which deep learning purveys nearly any use case, it's clear 2018 is the year this technology's utility will finally supersede classic machine learning's. "Traditional machine learning is more like statistics," indico CEO Tom Wilde reflected.