Healthcare analytics powered by medical images

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1 Healthcare analytics powered by medical images 14 Wall Street, 20th Flr, New York, NY

2 The Role of Images in Healthcare Analytics Healthcare analytics are a vital part of every hospital and are an important part of every strategic decision made by hospitals. Predictive analytics is the use of predictive models to predict future outcomes within specific certainty. An example would be: What is the re admission probability for this patient for the next 30 or 60 days? or What is the hospitalization probability for this outpatient within the next 1, 3 and 6 months? By leveraging specific patterns in the data we can build predictive algorithms that help hospitals better understand their population and become proactive. Hospitals can now anticipate results, instead of reacting only to the inflow of patients. To create these predictive models companies use available data from their Electronic Health Records and other sources such as the CMS data or open health data that many states have. These data are in text format (text and numbers) and are the only source of information that companies currently use to build predictive models. One of the biggest problems of the predictive analytics industry is that everybody is using only text to create the predictive models. However, the text represents only 5% of the total data, while more than 90% of the data is held in medical images. This presents a huge issue, as the accuracy of a predictive model is highly dependent on the amount and quality of data companies are using. Current models, by only using text, miss most of the data. Medical images is the untapped goldmine for more accurate predictive healthcare analytics By using images to create predictive models we are able to dig deeper into higher levels of granularity and accuracy. Let s see some examples to better understand the power of images on building predictive analytics solutions for healthcare.

3 EXAMPLE 1 Predictive hospital length of stay for patients with fractures of the hip Suppose that we need to be able to predict the length of stay for patients with fractured hip. The way these models are currently built is to take into account the type of the fracture, along with age and other comorbidities from the text of the electronic health record and use these info to build a predictive model. But what about the influence of the variety of the characteristics of the fracture on the length of stay? The text based categorization we currently use is very crude. In real life we encounter a large variety of hip fractures. Let s see some examples of hip fractures in X-ray images. Being able to include the universe of different image features of hip fractures to accurately predict the length of stay in the hospital has tremendous difference on the accuracy of the predictive models. At Nanotech Galaxy we use best in class artificial intelligence called deep learning. This technology allows us to include the different features of every fractures in our predictive models. The result? Much more granular and predictive power over the length of stay.

4 EXAMPLE 2 The influence of lung tumor shape on the response to chemotherapy The potential of deep learning technology is revolutionary for healthcare. We are able to create predictive models that are beyond the reach of current text based predictive modelling. Let s look into an example of different lung tumor images. The shapes and features of lung tumors can be very diverse. How about being in a position to predict, with high accuracy, the response to specific chemotherapeutics based on the analysis of the images? By using deep learning we are in position to mine the data of response to chemotherapy and also the survival curves from historical patients and then correletate these data with the image features of the tumors. This in not possible with current analytics that are based only on text. Result: We are in position to predict with a high level confidence the response to chemotherapy and survival curve of future patients by including the imaging of their lung tumor. This type of image based predictive analytics is the future of medicine and how healthcare will soon be delivered. Granular, personalised, predictive and preventive.

5 EXAMPLE 3 Finding similar past cases based on specific image parts How about being able to highlight a specific part of the medical image and being in a position to find similar images from the archive based only on the image similarity? This is a technology with a disruptive potential as: i) Diagnostic aid (consulting similar past cases helps when diagnosing a new border line or ambiguous case). ii) iii) Educational aid. Students and residents have instant access to all past similar cases and variations of those. Research aid. Being in a position to fetch similar images with the one highlighted is very important to reduce the time needed to collect previous cases for research purposes. At Nanotech Galaxy we develop technology that is automatically indexing your medical images archive and allows you to retrospectively search your PACS for similar images in the historical archive based only on image similarity. This is a very powerful technology that unlocks the value hidden on the storage of your medical images.

6 Nanotech Galaxy Founded by a vascular surgeon who left his career in surgery to become an artificial intelligent researcher, Nanotech Galaxy is empowering hospitals to become proactive organisations. We are using state of the art big data analytics and best in class artificial intelligence (deep learning) to unlock the goldmine of knowledge hidden in your data so that you can make the important decisions. We analyse all your data including medical images and create very powerful predictive algorithms that can help you We analyse all your data including medical images and create very powerful predictive algorithms that help you anticipate and prevent, rather than be surprised and react. Be in the forefront of healthcare analytics with our best in class artificial intelligence Our promise to you: Understand - Predict Prevent For any queries or to arrange a demo please contact us at Telephone: connect@nanotechgalaxy.com