Tagging cancer recurrence through machine learning
Who is this presentation for?
- C-level and midmanagement, operators, site engineers, and IT engineers
The possibility of cancer recurrence in a patient is difficult to predict with insurance-level information. Electronic health record (EHR) data contains multiple facets of patient history that, when combined and viewed from a patient representation perspective, can highlight the encounter where a recurrence was discovered. Appropriately tagging and identifying these recurrences as they occur opens up opportunities to understand which factors lead to recurrence.
Asif Hasan and Adam Hammond dive into how Quantiphi’s machine learning expertise alongside scalable services like BigQuery, DataProc, and CMLE helped a healthcare provider develop a solution designed to predict the recurrence of cancer in patients and recommend appropriate medical care.
- A basic understanding of computer vision
What you'll learn
- Learn how scalable services like BigQuery, DataProc, and CMLE helped a healthcare provider to develop a solution designed to predict the patient encounters associated with recurrence of cancer
Asif Hasan is the cofounder of Quantiphi, a category-defining applied AI and big data software and services provider. He has over 15 years of experience in technology services, healthcare, and financial services industries working on a variety of initiatives such as building applied AI and advanced analytics capabilities at a global scale, postmerger integration, supply-chain operations, business transformation, and professional services. Previously, Asif led a global team of analytics and data science professionals focused on developing leading-edge analytical algorithms and solutions for business decision support for a multi-billion-dollar global healthcare services business including customer experience, service delivery, supply chain, and professional services. He holds an MBA from McCallum Graduate school of Business at Bentley University and participated in executive education programs at Harvard Business School.
Adam Hammond is a solution architect at Quantiphi, a deep learning and artificial intelligence solutions company, where he’s actively involved in developing and delivering solutions in the healthcare and insurance industries (both of which often call for interpretable models). Adam holds an MBA from Bentley University and an undergraduate degree in economics.
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