I N D U S T R Y I N V E S T I G A T I O N diagnostic imaging that makes the most of the resources available , efficiencies can be gained , error rates reduced and workload capacity augmented .
Automated features are simple MedTech advancements that can help a radiographer with patient positioning , procedural consideration and accurate image acquisition . Automation also assists with radiology reporting tasks , first review triage or flagging scans of concern , worklist prioritisation and even diagnosis in routine work . This can help speed up treatment decision making , improving productivity and automatically reducing workload . At the same time , patient appointment times can be shortened to provide more slots during working hours to help battle the long waiting lists .
In emergency medicine , AI-assisted diagnostic tools can help with heavy workloads . For example , Auto Emergency has been designed to optimise treatment outcomes for A & E cases when speed and accuracy are crucial . This comprises stroke and chest pain modules that swiftly and automatically categorise images to detect signs of ischemic and haemorrhagic stroke in minutes or triage lifethreatening acute chest pain for pulmonary embolism or aortic dissection .
Understand more accurately what is needed in proactive healthcare
Accelerating the capabilities of AI through analysing UK health data will also deliver huge benefits to patients when it comes to detecting health population problems early and , before symptoms present .
Screening programmes are hugely successful – it is noted that 10,000 lives a year are saved through prevention and early diagnosis . So , imagine the potential quality of life that could be saved if more people were seen and targeted by understanding disease prevalence in more detail following data analysis by postcode or patient profile .
The power of unlocking data and using AI to identify normal scans quickly among largescale screening cohorts would also greatly assist the human-power behind radiological reporting . It could speed up the delivery of results to patients and streamline entire initiatives to reach greater numbers of people , separating out inconclusive results to be traditionally reviewed by radiologists .
Our work in unlocking data is already being advanced through the Safe-Haven Artificial Intelligence Platform ( SHAIP ) collaborations with industry partners , leading universities and NHS Trusts in Scotland . This progress is to be expanded in 2023 with national scaling of the SHAIP initiative and more regional locations added across primary and secondary care including NHS hospital Trusts , Integrated Care Systems ( ICS ), Community Diagnostic Centres ( CDCs ) and independent healthcare service providers . This will build on the diversity of data already collected to ultimately build a truly representative picture of the UK health population .
It ’ s here , it ’ s real and it ’ s progressive . Data is the remedy to many ills in our healthcare system . �
Mark Hitchman , Managing Director of Canon Medical Systems UK
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