Roberto Magnani
We ‘ll cover here the effect of AI in some application for Life Science industry. We are in the 4th industrial revolution: new technologies like AI, IOT, data and cloud are fundamentally altering the way we live, work and relate to each other. Specifically in healthcare now, with a better ability to integrate and harness the data from wearables, electronic health records, patient reported outcomes, genomics data, we can drive better actionable insights, with more efficient processes, faster decision making, smarter business, ending ultimately bringing new and more personalized medicines to patients sooner. The Life Science industry is still facing the challenges of the past. Clinical Trials, 80% of trials in the US fail to meet recruitment deadlines and more than 80% experience delays. It takes a lot of time and cost a lot to deliver a drug to the market, which inevitably affects the number of treatments we do get to the market. In addition Siloed and unstructured data collection across disparate systems makes it difficult and time consuming. It’s not about collecting or finding data anymore, its actually what do we do with the data. With AI we’ can analyze the data to derive actionable insights. The AI can process enormous amounts of structured and unstructured data, can understand natural language, including clinical text, to surface insights, reach conclusions and anticipate problems with human – level expertise. Industry real cases( i.e. project with Majo Clinic in Minnesota for edical coding improvement) show how training Watson and infuse it’s capability we have a significant improvement in rpecison and reduction of costs and time. With case we will arrive to show that. The pace of change will vary across industries but if we adopt these emerging, advanced technologies in the Life Science space we have a chance to bridge to the needs of yesterday and tomorrow and drive value and scalability to our patients and organizations.
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