The Deep Learning system market is exploding as the range of use cases across industry sectors expands. Emergen Research projects the global Deep Learning system market size will reach $93.45 billion by 2028. Driving this growth is adoption of cloud-based technology and the use of Deep Learning systems in big data analytics, as well as the increasing deployment of smart cities technologies used to perform tasks like monitoring traffic patterns and energy systems management to keep environments safe.
Technology has altered nearly every aspect of healthcare delivery.
New devices improve patient diagnosis and treatment. New advances in robotics make surgeries less invasive and more precise. Sensors and wearables are widely used to improve health and wellness. Cutting edge research is helping us understand how the human body works and enables genome sequencing, for instance, to provide valuable information on drug sensitivity and genetic predisposition to specific illness. And in the age of COVID-19, technology has enabled telemedicine and remote health monitoring tools.
Deep Learning applications are also impacting healthcare in myriad ways, including enabling faster and more accurate diagnostics and reducing administrative tasks to free professionals to work on their core competencies. Ultimately, it helps providers and payors reduce the cost of care and improve patient outcomes.
While Deep Learning is an important technology for most sectors, it is transformative for healthcare.
Here are some of the most compelling Deep Learning use cases specifically in the area of patient care.
Additional applications of Deep Learning include improving fraud detection, boosting customer and member engagement, tracking provider quality and performance monitoring.