214 citations · 442 across the 48 of their papers we have counts for
6 papers · 1 filter
Voting of predictive models for clinical outcomes: consensus of algorithms for the early prediction of sepsis from clinical data and an analysis of the PhysioNet/Computing in Cardiology Challenge 2019
Matthew A. Reyna, Gari D. Clifford
Although there has been significant research in boosting of weak learners, there has been little work in the field of boosting from strong learners. This latter paradigm is a form…
Deep Sequence Learning for Accurate Gestational Age Estimation from a 25 Doppler Device
Nasim Katebi, Reza Sameni, Gari D. Clifford
Assessing fetal development is usually carried out by techniques such as ultrasound imaging, which is generally unavailable in rural areas due to the high cost, maintenance, skills…
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…
The Future AI in Healthcare: A Tsunami of False Alarms or a Product of Experts?
Gari D. Clifford
Recent significant increases in affordable and accessible computational power and data storage have enabled machine learning to provide almost unbelievable classification and predi…
Remote health monitoring and diagnosis in the time of COVID-19
Joachim A. Behar, Chengyu Liu, Kevin Kotzen +13
Coronavirus disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that is rapidly spreading across the globe. The clinical spectrum of SA…
Temporal-Framing Adaptive Network for Heart Sound Segmentation without Prior Knowledge of State Duration
Xingyao Wang, Chengyu Liu, Yuwen Li +3
Objective: This paper presents a novel heart sound segmentation algorithm based on Temporal-Framing Adaptive Network (TFAN), including state transition loss and dynamic inference f…