3 citations · 3 across the 9 of their papers we have counts for
11 papers
Calibration-Free Cuffless Blood Pressure Estimation Using Multimodal ECG-PPG Fusion on a Google Pixel Watch
Jathushan Kaetheeswaran, Boyi Ma, Ali Abedi +2
Inadequate blood pressure (BP) monitoring and management outside of clinical settings can worsen major cardiovascular risk factors such as hypertension. While cuff-based devices ar…
HEART-Watch: A multimodal physiological dataset from a Google Pixel Watch across different physical states
Jathushan Kaetheeswaran, Boyi Ma, Ali Abedi +2
Consumer-grade smartwatches offer a new option for personalized health monitoring for general consumers, as cardiovascular diseases continue to prevail as the leading cause of glob…
Classifying Clinical Outcome of Epilepsy Patients with Ictal Chirp Embeddings
Nooshin Bahador, Milad Lankarany
This study presents a pipeline leveraging t-Distributed Stochastic Neighbor Embedding (t-SNE) for interpretable visualizations of chirp features across diverse outcome scenarios. T…
Semi-Supervised Anomaly Detection Pipeline for SOZ Localization Using Ictal-Related Chirp
Nooshin Bahador, Milad Lankarany
This study presents a quantitative framework for evaluating the spatial concordance between clinically defined seizure onset zones (SOZs) and statistically anomalous channels ident…
Chirp Localization via Fine-Tuned Transformer Model: A Proof-of-Concept Study
Nooshin Bahador, Milad Lankarany
Spectrograms are pivotal in time-frequency signal analysis, widely used in audio processing and computational neuroscience. Chirp-like patterns in electroencephalogram (EEG) spectr…
Agentic Medical Knowledge Graphs Enhance Medical Question Answering: Bridging the Gap Between LLMs and Evolving Medical Knowledge
Mohammad Reza Rezaei, Reza Saadati Fard, Jayson L. Parker +2
Large Language Models (LLMs) have significantly advanced medical question-answering by leveraging extensive clinical data and medical literature. However, the rapid evolution of me…
Stochastic Sparse Sampling: A Framework for Variable-Length Medical Time Series Classification
Xavier Mootoo, Alan A. Díaz-Montiel, Milad Lankarany +1
While the majority of time series classification research has focused on modeling fixed-length sequences, variable-length time series classification (VTSC) remains critical in heal…
Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling
Mohammad R. Rezaei, Milos R. Popovic, Milad Lankarany +1
Conditional Flow Matching (CFM) models can generate high-quality samples from a non-informative prior, but they can be slow, often needing hundreds of network evaluations (NFE). To…
Uncovering the Origins of Instability in Dynamical Systems: How Attention Mechanism Can Help?
Nooshin Bahador, Milad Lankarany
The behavior of the network and its stability are governed by both dynamics of individual nodes as well as their topological interconnections. Attention mechanism as an integral pa…
Deep Direct Discriminative Decoders for High-dimensional Time-series Data Analysis
Mohammad R. Rezaei, Milos R. Popovic, Milad Lankarany +1
The state-space models (SSMs) are widely utilized in the analysis of time-series data. SSMs rely on an explicit definition of the state and observation processes. Characterizing th…
Gradient-Free Neural Network Training via Synaptic-Level Reinforcement Learning
Aman Bhargava, Mohammad R. Rezaei, Milad Lankarany
An ongoing challenge in neural information processing is: how do neurons adjust their connectivity to improve task performance over time (i.e., actualize learning)? It is widely be…