no code implementations • 14 Nov 2022 • Ying Xu, Romane Gauriau, Anna Decker, Jacob Oppenheim
Understanding patterns of diagnoses, medications, procedures, and laboratory tests from electronic health records (EHRs) and health insurer claims is important for understanding disease risk and for efficient clinical development, which often require rules-based curation in collaboration with clinicians.
no code implementations • 14 Nov 2022 • David A. Bloore, Romane Gauriau, Anna L. Decker, Jacob Oppenheim
Electronic health records (EHR) are widely believed to hold a profusion of actionable insights, encrypted in an irregular, semi-structured format, amidst a loud noise background.
no code implementations • 19 Aug 2020 • Giorgio Pietro Biondetti, Romane Gauriau, Christopher P. Bridge, Charles Lu, Katherine P. Andriole
Recognition of such bias is critical to develop robust, generalizable models that will be crucial for clinical applications in real-world data distributions.
no code implementations • 2 Mar 2020 • Charles Lu, Julia Strout, Romane Gauriau, Brad Wright, Fabiola Bezerra De Carvalho Marcruz, Varun Buch, Katherine Andriole
Healthcare is one of the most promising areas for machine learning models to make a positive impact.
no code implementations • 29 Oct 2019 • Neil Deshmukh, Selin Gumustop, Romane Gauriau, Varun Buch, Bradley Wright, Christopher Bridge, Ram Naidu, Katherine Andriole, Bernardo Bizzo
Although machine learning has become a powerful tool to augment doctors in clinical analysis, the immense amount of labeled data that is necessary to train supervised learning approaches burdens each development task as time and resource intensive.