Tuning In: Analysis of Audio Classifier Performance in Clinical Settings with Limited Data

no code implementations • 7 Feb 2024 • Hamza Mahdi, Eptehal Nashnoush, Rami Saab, Arjun Balachandar, Rishit Dagli, Lucas X. Perri, Houman Khosravani

This study assesses deep learning models for audio classification in a clinical setting with the constraint of small datasets reflecting real-world prospective data collection.

Audio Classification Model Selection +1

Can Self Reported Symptoms Predict Daily COVID-19 Cases?

1 code implementation • 18 May 2021 • Parth Patwa, Viswanatha Reddy, Rohan Sukumaran, Sethuraman TV, Eptehal Nashnoush, Sheshank Shankar, Rishemjit Kaur, Abhishek Singh, Ramesh Raskar

The models are developed at two levels of data granularity - local models, which are trained at the state level, and a single global model which is trained on the combined data aggregated across all states.