New Medical Imaging technology in Radiology


it was first introduced as a concept in the medical profession, artificial
intelligence has been eyed with suspicion. Many professionals have been
concerned that it will be used to replace their expertise and potentially
negatively impact on patient care and results.

real value of AI lies in how it are often
collaboration with the radiologist or medical
professional. In how it can be used to enhance and support the professional by
streamlining process, reducing the diagnosis burden, and improving workflow
efficiency. Artificial intelligence in radiology may be a tool,
not a sentient being. It is an investment into technology that
for ongoing improvements to diagnosis and patient
care by supporting the radiologist as they battle increasingly weighty

in 2015, a survey published in Academic Radiology found that radiologists need
to review one image every 3-4 seconds to keep up with their workloads. There’s
little research highlighting how much heavier these workloads have become over
the past five years, but it is very likely to be even more demanding today.

Why Add AI in Radiology ?

intelligence in radiology is becoming an increasingly integral part of the
profession and daily life. Often described as that extra team member, the one
that never sleeps or gets tired and can sift through images without pause, AI
adds immense value. It has become slowly embedded into numerous medical
institutions globally, filtering into workflows and systems, and being
customized to match radiologist requirements. 

algorithms have advanced to the purpose
where they
absolutely support clinician deciding
. Global Diagnostics Australia (GDA), was one of the
first diagnostic imaging companies in Australia to include AI as part of its
radiology workflow and it achieved notable results. The high-end algorithms
were incorporated into the care management pathway to expedite patient
diagnosis and treatment across the head, chest and neck. The AI solution was
designed to prioritize patients according to their critical status, alerting
the radiologist to urgent cases and reshaping their approach to workflow and

Use of AI in Radiology

has the ability to pick up enough of the image diagnosis weight so that the
radiologist can focus on the complex cases that require their specialist
attention. It can effectively triage the urgent cases and streamline the
process in the face of increased pressure from both the medical facilities and
regulatory institutions.

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