While all our IP is owned by the company and all research happens in-house, current team members have published widely in public peer-reviewed journals on underlying principles and adjacent fields as part of previous or ongoing academic careers. Below are some papers previously published or co-published by Decorte Future Industries team members, as part of their membership of various research groups or during doctoral research, exploring and validating various methods of health data gathering using audio.

The papers listed below are a mostly random selection; a complete list of papers can be found on relevant team members’ research pages: Erika Bondareva, Kayla Butkow, Vijay Vignesh Venkataramani. Erika Bondareva and Kayla Butkow’s academic work has been primarily associated with the University of Cambridge’s Department of Computer Science and Technology, including collaborations with Nokia Bell Labs. Vijay Venkataramani’s work has been primarily associated with the Center for Computational Natural Sciences and Bioinformatics at IIIT Hyderabad.

“Exploring longitudinal cough, breath, and voice data for COVID-19 progression prediction via sequential deep learning: model development and validation”, Journal of medical Internet research 24 (6), e37004

Authors: Ting Dang, Jing Han, Tong Xia, Dimitris Spathis, Erika Bondareva, Chloë Siegele-Brown, Jagmohan Chauhan, Andreas Grammenos, Apinan Hasthanasombat, R Andres Floto, Pietro Cicuta, Cecilia Mascolo.

“Stress Inference from Abdominal Sounds using Machine Learning”, 2022, arXiv:2201.01232

Authors: Erika Bondareva, Marios Constantinides, Michael S Eggleston, Ireneusz Jabłoński, Cecilia Mascolo, Zoran Radivojevic, Sanja Šćepanović.

“Sounds of COVID-19: exploring realistic performance of audio-based digital testing”, 2022, Nature Partner Journal Digital Medicine 5, 1-9.

Authors: Jing Han, Tong Xia, Dimitris Spathis, Erika Bondareva, Chloë Brown, Jagmohan Chauhan, Ting Dang, Andreas Grammenos, Apinan Hasthanasombat, Andres Floto, Pietro Cicuta & Cecilia Mascolo.

“COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening”, 2021, 35th Conference on Neural Information Processing Systems and Datasets and Benchmarks Track

Authors: Tong Xia, Dimitris Spathis, J Ch, Andreas Grammenos, Jing Han, Apinan Hasthanasombat, Erika Bondareva, Ting Dang, Andres Floto, Pietro Cicuta, Cecilia Mascolo.