The increasing availability of biomedical data from large biobanks, electronic health records,
medical imaging, wearable and ambient biosensors, and the lower cost of genome and …

With the recent advancement of novel biomedical technologies such as high-throughput
sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics …

Objective In applying machine learning (ML) to electronic health record (EHR) data, many
decisions must be made before any ML is applied; such preprocessing requires substantial …

Early detection of preventable diseases is important for better disease management,
improved interventions, and more efficient health-care resource allocation. Various machine …

Recently, researchers have started applying convolutional neural networks (CNNs) with one-
dimensional convolutions to clinical tasks involving time-series data. This is due, in part, to …

We seek to predict knee and ankle motion using wearable sensors. These predictions could
serve as target trajectories for a lower limb prosthesis. In this manuscript, we investigate the …

Electroencephalography (EEG)-based depression detection has become a hot topic in the
development of biomedical engineering. However, the complexity and nonstationarity of …

Early detection of cancer is a significant unmet clinical need. Improved technical ability to
detect circulating tumor-derived DNA (ctDNA) in the cell-free DNA (cfDNA) component of …

Miniaturized and wearable sensor-based measurements enable the assessment of
Parkinson's disease (PD) motor-related features like never before and hold great promise as …

In this paper, we analyze the millions of referral paths of patients' interactions with the
healthcare system for each year in the 2006-2011 time period and relate them to US …