Henrik Müller

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The foundation for the establishment of Enablement has been a desire to combine business understanding with the opportunities that AI/ML brings. Digitalisation and AI have been in focus for the last years, but few companies have generated value through the new possibilities. The main reason being that the companies are not able to identify relevant business challenges and identify the right new technology to include the right data to generate new value for companies and customers. Enablement helps customers get the right strategy, organisation and technology in place to ensure value creation utilising AI/ML. Our starting point is to ensure that the management gets the right understanding of the strategic potential to formulate the strategy for AI. We recommend in parallel with the strategic process to have AI PoC running to ensure a right anchoring in the business and to ensure a real understanding of the baseline for the strategy – and last but not least – to create the first value utilising AI/ML. The methodology for solving is; Scientific method of reasoning applied to data. Hypothesis and experiments even though a project’s key goal — development and deployment of a predictive model etc. — is achieved, a project continues. We are never “done”, we enter a partnership with our customers. Data scientists have to monitor if the accuracy of forecasting results corresponds to performance requirements and improve a model if needed. So being explorative after the first project is what is going to happen. Placing the project in an economic context, identifying its expected benefits and balancing that with its costs and risks. Move from Research to Development via POC’s. Using an incremental project investment approach, which includes regular project reviews against the economic model defined for the project. This will make the whole project more transparent, and the customer will be more at ease with potential “risks”.

Cerebriu’s proven radiology AI solutions detect findings during the initial scan and enable the most appropriate procedures while the patient is still in the scanner. This leads to a simpler, faster MR image acquisition and creates tangible clinical value: Improving technologists’ confidence and freeing up radiologists’ time by ensuring the right data the first time the patient is in the scanner Timely diagnosis of critical findings by prioritizing radiologists’ worklists Improving patient experience and reducing patient recalls