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Principal Investigator
Shawn Stapleton
Philips Research North America
Position Title
Senior Data Scientist
About this CDAS Project
NLST (Learn more about this study)
Project ID
Initial CDAS Request Approval
Sep 16, 2016
Improved lung cancer screening with cognitive computing
Every year, 200,000 people are diagnosed with lung cancer resulting in 160,000 deaths per year (450 people per day) in the US alone. Early detection can increase the five-year survival rate for stage 1 lung cancer to nearly 90%. Screening patients with low-dose computed tomography (LDCT) has been proven to find lung cancer at its earliest stages ad reduce mortality. As a result, the number of lung cancer screenings by LDCT is expected to increase rapidly.

To address this new paradigm, we plan to leverage rich, high level features with deep learning and context with joint modeling such that clinicians and hospitals can provide optimal lung cancer screening both in terms of patient outcomes and clinical workflow. To achieve this goal we plan to leverage algorithms built from the largescale, multi-site observational NLST dataset. With this rich information, we test the feasibility of improving the differentiation of an individual patient’s risk, assisting clinicians in directing patients to optimal clinical care, and providing that information in an automated fashion to fits seamlessly in clinical workflow.

Aim 1: Develop Automated algorithms to reduce time and cognitive load for radiologists
Aim 2: Improve predictive strength such that unnecessary escalation and resultant complications due to false positives reads and overdiagnosis are prevented.
Aim 3: Develop algorithms that can handle high dimensionality data from radiology and digital pathology and provide improved prognostic indicators of malignancy.


Teun Heuvel, Philips Research Eindhoven
Arkadiusz Sitek, Philips Research North America
Tobias Klinder, Philips Research Hamburg
Rafael Wiemker, Philips Research Hamburg
Amir Tahmasebi, Philips Research North America
Sandeep Dalal, Philips Research North America

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