GE Healthcare presents how Data and Artificial Intelligence can help in elevating and shaping the future of healthcare and break down traditional silos

GE Healthcare has presented its digital solutions at an event entitled GE Healthcare Dialogues – Elevating Digital Healthcare and has highlighted the digital transition challenges in the healthcare sector. Held at Dusit Thani Lakeview in Cairo, the event was attended by the Ministry of Health representatives, GE Healthcare’s partners and customers from the public and private sectors, and key opinion leaders.
During the conference, experts discussed the challenges being faced in different areas like radiology and cardiology, looking at how digital is helping to revolutionize the traditional scope and ways of working in these areas.
GE Healthcare introduced several solutions and demonstrated their impact in breaking down traditional silos across departments, hospitals and entire cities:
-AW Server Enterprise used in radiology, a platform for an efficient and automated workflow, allowing better time, equipment, costs and resources management, while enhancing team’s ability to collaborate and provide a diagnosis.
-Centricity Cardio Enterprise used in cardiology. A comprehensive IT solution that offers cardiologists a single point of access to patient data, images and reports across the continuum of care while enhancing physician productivity and improving charge capture accuracy.
-Centricity 360 is a collaboration tool that enables intuitive yet advanced clinician collaboration, seamless medical device connectivity and embedded healthcare analytics – all with comprehensive end user controls and data management.
AI was also discussed during the conference. AI in healthcare has seen a significant rise over the last couple of years, especially in radiology explained Amro Kandil, General Manager, GE Healthcare in North East Africa. The 2017 PwC DIQ Survey found that 39% of healthcare managers were planning to invest in artificial intelligence, which indicates its rapid growth. Through the use of AI and machine learning, we see a future where the combination of in-vivo and in-vitro data sets can provide new insights on the underlying causes of disease , he added.

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