Meena M. Makary, Pablo Polosecki, et al.
PNAS
We conducted a feasibility analysis to determine the quality of data that could be collected ambiently during routine clinical conversations. We used inexpensive, consumer-grade hardware to record unstructured dialogue and open-source software tools to quantify and model face, voice (acoustic and language) and movement features. We used an external validation set to perform proof-of-concept predictive analyses and show that clinically relevant measures can be produced without a restrictive protocol.
Meena M. Makary, Pablo Polosecki, et al.
PNAS
Shifali Singh, Lisa Kluen, et al.
JMIR Formative Research
Katsuyuki Sakuma, Bucknell Webb, et al.
ECTC 2019
Carla Agurto, Mary Pietrowicz, et al.
EMBC 2020