Theodoros Zanos

Assistant Professor, Head of Neural and Data Science Lab

Northwell Health Feinstein Institutes for Medical Research

United States

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Dr. Theodoros Zanos is an Assistant Professor and the Head of the Neural and Data Science Lab at Northwell Health Feinstein Institutes for Medical Research. He conducts research primarily in the fields of neural representation, machine learning applications in medical diagnostics, and the exploration of vagal nerve stimulation techniques. His recent publications include studies on antiphospholipid syndrome, predictive modeling in hematology, and the optimization of neuromodulation therapies. Dr. Zanos is based in the United States.

Articles (20)

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Collaborators (7)

Sangeeta S. Chavan

Professor

Northwell Health Feinstein Institutes for Medical Research

UNITED STATES

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Umair Ahmed

Feinstein Institute for Medical Research

UNITED STATES

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Stavros Zanos

Associate Professor

Northwell Health Feinstein Institutes for Medical Research

UNITED STATES

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Brian Ward

Professor

McGill University Health Centre

CANADA

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Eric Chang

Assistant Professor

Feinstein Institute for Medical Research

UNITED STATES

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Timir Datta-Chaudhuri

Assistant Professor

Feinstein Institute for Medical Research

UNITED STATES

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Loren Rieth

Associate Professor

West Virginia University

UNITED STATES

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Theodoros Zanos

Research Interests

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About

Articles (20)

Understanding primary antiphospholipid syndrome: Analyzing antiphospholipid antibody profile and titers correlation to hematological activity and development of predictive models.

Neural representation of cytokines by vagal sensory neurons.

TraNscutaneOus Electrical VAgus Nerve Stimulation to Suppress Premature Ventricular Contractions: A Crossover, Randomized Clinical Trial (NoVa-PVC).

PO-05-035 UNLOCKING ATRIAL FIBRILLATION PREDICTION: A MACHINE LEARNING APPROACH POWERED BY IMPLANTABLE CARDIOVERTER-DEFIBRILLATOR DEVICE PARAMETERS

PO-07-209 TRANSCUTANEOUS ELECTRICAL VAGUS NERVE STIMULATION TO SUPPRESS PREMATURE VENTRICULAR CONTRACTIONS: A CROSS-OVER, RANDOMIZED CLINICAL TRIAL (NOVA-PVC)

Fascicular Organization and Fiber Composition of the Human Vagus Nerve at Levels of Branch Emergence

IS091 DECIPHERING VAGAL ANATOMY AND BRAIN-BODY SIGNALING TO OPTIMIZE NEUROMODULATION THERAPIES

A Systematic Review of the Applications of Deep Learning for the Interpretation of Positron Emission Tomography Images of Patients with Lymphoma

Machine learning to predict completion of treatment for pancreatic cancer.

Forecasting Hematological Activity in Antiphospholipid Syndrome Using Predictive Models

Calcium imaging and analysis of the jugular-nodose ganglia enables identification of distinct vagal sensory neuron subsets

A radiographic, deep transfer learning framework, adapted to estimate lung opacities from chest x-rays

Prediction of intrapartum fever using continuously monitored vital signs and heart rate variability

High Frequency of COVID-19 Vaccine Hesitancy among Canadians Immunized for Influenza: A Cross-Sectional Survey

A method to quantify autonomic nervous system function in healthy, able-bodied individuals

A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation

External validation demonstrates limited clinical utility of the interpretable mortality prediction model for patients with COVID-19

Towards Personalized Closed-Loop Mechanical CPR: A Model Relating Carotid Blood Flow to Chest Compression Rate and Duration

An impedance matching algorithm for common-mode interference removal in vagus nerve recordings

Anodal block permits directional vagus nerve stimulation

Collaborators (7)

Sangeeta S. Chavan

Umair Ahmed

Stavros Zanos

Brian Ward

Eric Chang

Timir Datta-Chaudhuri

Loren Rieth

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