Agfa HealthCare Highlights Augmented Intelligence Approach at Arab Health
By HospiMedica International staff writers
Posted on 28 Jan 2019
Agfa HealthCare (Mortsel, Belgium) demonstrated its approach of building an ecosystem of Augmented Intelligence at Arab Health 2019 that is powered by Machine Learning, Cognitive Reasoning and Task-based rules engine to help enable delivery of innovative solutions for enhancing care delivery.Posted on 28 Jan 2019
Agfa HealthCare is a provider of eHealth & Digital Imaging solutions that optimize the efficiency of care organizations and improve patient care. Medical imaging is witnessing a revolution driven by digital transformation initiatives and the availability of advanced clinical applications. New imaging techniques are providing greater anatomical and clinical details to radiologists, cardiologists, oncologists, and other diagnosticians, indicating the need for quicker access to imaging reports and results, collaborative workflows and Augmented Intelligence.
Augmented Intelligence is the intersection of machine learning and advanced applications, where clinical knowledge and medical data converge on a single platform. Augmented Intelligence can reduce the workload of health imaging experts as well as improve their performance. The potential benefits of Augmented Intelligence can be realized when it is used in the context of workflows and systems that healthcare practitioners operate and interact with. Unlike Artificial Intelligence, which tries to replicate human intelligence, Augmented Intelligence works with and amplifies human intelligence.
Agfa HealthCare Enterprise Imaging platform is standards-based, designed for interoperability and enables a leading-edge approach to seamlessly embed machine learning algorithms. With these algorithms, healthcare providers will have the ability to view contextual images and optimize screening workflows. Physicians will also be able to enjoy quicker access to critical results, helping lower wait times and improve referral services for cases requiring urgent patient care coordination.