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3,315 results on '"Asirvatham, Samuel"'

3. HypUC: Hyperfine Uncertainty Calibration with Gradient-boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms

Author

Upadhyay, Uddeshya, Bade, Sairam, Puranik, Arjun, Asfahan, Shahir, Babu, Melwin, Lopez-Jimenez, Francisco, Asirvatham, Samuel J., Prasad, Ashim, Rajasekharan, Ajit, Awasthi, Samir, and Barve, Rakesh

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computational Engineering, Finance, and Science, Statistics - Applications
Abstract

The automated analysis of medical time series, such as the electrocardiogram (ECG), electroencephalogram (EEG), pulse oximetry, etc, has the potential to serve as a valuable tool for diagnostic decisions, allowing for remote monitoring of patients and more efficient use of expensive and time-consuming medical procedures. Deep neural networks (DNNs) have been demonstrated to process such signals effectively. However, previous research has primarily focused on classifying medical time series rather than attempting to regress the continuous-valued physiological parameters central to diagnosis. One significant challenge in this regard is the imbalanced nature of the dataset, as a low prevalence of abnormal conditions can lead to heavily skewed data that results in inaccurate predictions and a lack of certainty in such predictions when deployed. To address these challenges, we propose HypUC, a framework for imbalanced probabilistic regression in medical time series, making several contributions. (i) We introduce a simple kernel density-based technique to tackle the imbalanced regression problem with medical time series. (ii) Moreover, we employ a probabilistic regression framework that allows uncertainty estimation for the predicted continuous values. (iii) We also present a new approach to calibrate the predicted uncertainty further. (iv) Finally, we demonstrate a technique to use calibrated uncertainty estimates to improve the predicted continuous value and show the efficacy of the calibrated uncertainty estimates to flag unreliable predictions. HypUC is evaluated on a large, diverse, real-world dataset of ECGs collected from millions of patients, outperforming several conventional baselines on various diagnostic tasks, suggesting a potential use-case for the reliable clinical deployment of deep learning models., Comment: Published at TMLR

Published
2023

4. Vagus nerve stimulation using an endovascular electrode array.

Author

Nicolai, Evan, Larco, Jorge, Madhani, Sarosh, Asirvatham, Samuel, Chang, Su-Youne, Ludwig, Kip, Savastano, Luis, and Worrell, Gregory

Subjects
electroneurography, endovascular, intravascular, minimally invasive, neuromodulation, swine, vagus nerve stimulation (VNS), Animals, Swine, Vagus Nerve Stimulation, Vagus Nerve, Electrodes, Implanted, Evoked Potentials, Nerve Fibers
Abstract

Objective. Vagus nerve stimulation (VNS), which involves a surgical procedure to place electrodes directly on the vagus nerve (VN), is approved clinically for the treatment of epilepsy, depression, and to facilitate rehabilitation in stroke. VNS at surgically implanted electrodes is often limited by activation of motor nerve fibers near and within the VN that cause neck muscle contraction. In this study we investigated endovascular VNS that may allow activation of the VN at locations where the motor nerve fibers are not localized.Approach. We used endovascular electrodes within the nearby internal jugular vein (IJV) to electrically stimulate the VN while recording VN compound action potentials (CAPs) and neck muscle motor evoked potentials (MEPs) in an acute intraoperative swine experiment.Main Results. We show that the stimulation electrode position within the IJV is critical for efficient activation of the VN. We also demonstrate use of fluoroscopy (cone beam CT mode) and ultrasound to determine the position of the endovascular stimulation electrode with respect to the VN and IJV. At the most effective endovascular stimulation locations tested, thresholds for VN activation were several times higher than direct stimulation of the nerve using a cuff electrode; however, this work demonstrates the feasibility of VNS with endovascular electrodes and provides tools to optimize endovascular electrode positions for VNS.Significance. This work lays the foundation to develop endovascular VNS strategies to stimulate at VN locations that would be otherwise too invasive and at VN locations where structures such as motor nerve fibers do not exist.

Published
2023

28. Determinants of Sudden Cardiac Death in Adult Patients With Eisenmenger Syndrome.

Author

Chiriac, Anca, Riley, David, Russell, Matthew, Moore, Jeremy, Padmanabhan, Deepak, Hodge, David, Spiegel, Matthew, Vargas, Emily, Phillips, Sabrina, Ammash, Naser, Madhavan, Malini, Asirvatham, Samuel, and McLeod, Christopher

Subjects
Eisenmenger syndrome, atrial fibrillation, cardiac arrhythmia, congenital heart disease, congestive heart failure, sudden cardiac death, Adult, Arrhythmias, Cardiac, Cause of Death, Death, Sudden, Cardiac, Eisenmenger Complex, Female, Florida, Humans, Los Angeles, Male, Middle Aged, Retrospective Studies, Risk Assessment, Risk Factors, Time Factors, Young Adult
Abstract

Background Patients with Eisenmenger syndrome are known to have a high incidence of sudden cardiac death (SCD), yet the underlying causes are not well understood. We sought to define the predictors of SCD in this population. Methods and Results A retrospective analysis of all patients with Eisenmenger syndrome from 2 large tertiary referral centers was performed. ECGs, prolonged ambulatory recordings, echocardiograms, and clinical histories were reviewed; and the cause of death was identified. A total of 246 patients (85 [34.6%] men) with a mean age of 37.3 (±14.2) years were followed up for a median of 7 years. Over the study period, 136 patients died, with 40 experiencing SCD and 74 experiencing cardiac death (sudden and nonsudden). Age, atrial fibrillation, prolonged QRS duration, complete heart block, right atrial enlargement, right bundle branch block, increased right atrial pressure, impaired biventricular function, and the presence of a pacemaker were associated with increased risk of SCD, whereas advanced pulmonary hypertension therapies were protective. Atrial fibrillation (11.45-fold increased risk; P

Published
2020

44. 2022 HRS expert consensus statement on evaluation and management of arrhythmic risk in neuromuscular disorders

Author

Groh, William J., Bhakta, Deepak, Tomaselli, Gordon F., Aleong, Ryan G., Teixeira, Ricardo Alkmim, Amato, Anthony, Asirvatham, Samuel J., Cha, Yong-Mei, Corrado, Domenico, Duboc, Denis, Goldberger, Zachary D., Horie, Minoru, Hornyak, Joseph E., Jefferies, John Lynn, Kääb, Stefan, Kalman, Jonathan M., Kertesz, Naomi J., Lakdawala, Neal K., Lambiase, Pier D., Lubitz, Steven A., McMillan, Hugh J., McNally, Elizabeth M., Milone, Margherita, Namboodiri, Narayanan, Nazarian, Saman, Patton, Kristen K., Russo, Vincenzo, Sacher, Frederic, Santangeli, Pasquale, Shen, Win-Kuang, Sobral Filho, Dario C., Stambler, Bruce S., Stöllberger, Claudia, Wahbi, Karim, Wehrens, Xander H.T., Weiner, Menachem Mendel, Wheeler, Matthew T., and Zeppenfeld, Katja

Published
2022
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47. Novel insights into the substrate involved in maintenance of ventricular fibrillation: results from continuous multipolar mapping in a canine model

Author

Ezzeddine, Fatima M., Ward, Robert C., Jiang, Zhi, Tri, Jason A., Agboola, Kolade, Hu, Tiffany, Lodhi, Fahad, Tan, Nicholas Y., Ladas, Thomas P., Christopoulos, Georgios, Sugrue, Alan M., Tolkacheva, Elena G., Munoz, Freddy Del-Carpio, McLeod, Christopher J., Asirvatham, Samuel J., and DeSimone, Christopher V.

Published
2022
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48. Ventricular nanosecond pulsed electric field delivery using active fixation leads: a proof-of-concept preclinical study

Author

Tan, Nicholas Y., Ladas, Thomas P., Christopoulos, Georgios, Sugrue, Alan M., van Zyl, Martin, Ladejobi, Adetola O., Lodhi, Fahad K., Hu, Tiffany Y., Ezzeddine, Fatima M., Agboola, Kolade, Uecker, Darrin, Maor, Elad, Tri, Jason A., Jiang, Zhi, Yasin, Omar Z., DeSimone, Christopher V., Killu, Ammar M., Asirvatham, Samuel J., and Del-Carpio Munoz, Freddy

Published
2022
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