6 citations · 8 across the 4 of their papers we have counts for
4 papers
Benchmarking changepoint detection algorithms on cardiac time series
Ayse Cakmak, Erik Reinertsen, Shamim Nemati +1
The pattern of state changes in a biomedical time series can be related to health or disease. This work presents a principled approach for selecting a changepoint detection algorit…
Late fusion of machine learning models using passively captured interpersonal social interactions and motion from smartphones predicts decompensation in heart failure
Ayse S. Cakmak, Samuel Densen, Gabriel Najarro +5
Objective: Worldwide, heart failure (HF) is a major cause of morbidity and mortality and one of the leading causes of hospitalization. Early detection of HF symptoms and pro-active…
Using Convolutional Variational Autoencoders to Predict Post-Trauma Health Outcomes from Actigraphy Data
Ayse S. Cakmak, Nina Thigpen, Garrett Honke +9
Depression and post-traumatic stress disorder (PTSD) are psychiatric conditions commonly associated with experiencing a traumatic event. Estimating mental health status through non…
Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates
Justus T. C. Schwabedal, John C. Snyder, Ayse Cakmak +2
Randomizing the Fourier-transform (FT) phases of temporal-spatial data generates surrogates that approximate examples from the data-generating distribution. We propose such FT surr…