Joseph Finkelstein

Professor

Icahn School of Medicine at Mount Sinai

United States

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About

Joseph Finkelstein is a Professor at the Icahn School of Medicine at Mount Sinai in the United States. His research areas include telemedicine, artificial intelligence in healthcare, and exercise interventions for various medical conditions. Recent articles explore topics such as the application of deep learning in cancer care and the usability of home automated systems for individualized exercise programs.

Articles (17)

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2023

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2023

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2022

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2021

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2021

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2020

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2020

Collaborators (6)

Kensaku Kawamoto

University of Utah

UNITED STATES

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Ramkiran Gouripeddi

University of Utah

UNITED STATES

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Alejandro Domínguez Rodríguez

University of Twente

NETHERLANDS

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Guilherme Del Fiol

Professor and Vice-Chair for Research

University of Utah

UNITED STATES

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Anas Elghafari

University of Maastricht

NETHERLANDS

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Fatemeh Shah Mohammadi

Research Assistant Professor

University of Utah

UNITED STATES

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Joseph Finkelstein

Research Interests

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About

Articles (17)

Telemedicine-Supported Exercise Interventions in Hematopoietic Stem Cell Transplantation: A Scoping Review

The Consistency of Hypercapnic Respiratory Failure Case Definitions in Electronic Health Record Data

Deep Learning Approaches to Forecast Physical and Mental Deterioration During Chemotherapy in Patients with Cancer

Exploring Artificial Intelligence Biases in Predictive Models for Cancer Diagnosis

Self-administered interventions based on natural language processing models for reducing depressive and anxious symptoms: Systematic review and meta-analysis (Preprint)

Dynamic Prediction of Physical Exertion: Leveraging AI Models and Wearable Sensor Data During Cycling Exercise

Home Automated Telemanagement System for Individualized Exercise Programs: Design and Usability Evaluation

Exercise Interventions in the Management of Postural Orthostatic Tachycardia Syndrome: A Scoping Review

AI-Driven Prediction of Symptom Trajectories in Cancer Care: A Deep Learning Approach for Chemotherapy Management

Addressing Semantic Variability in Clinical Outcome Reporting Using Large Language Models

Implementing Machine Learning in the Electronic Health Record: Checklist of Essential Considerations

Development and Evaluation of Wireless Interfaces to Monitor and Control Cycling Exercise During Home Telerehabilitation

Telemonitoring of Home-Based Biking Exercise: Assessment of Wireless Interfaces

Identification of Liver Cancer Stem Cell Stemness Markers Using a Comparative Analysis of Public Data Sets

Automated Identification of Common Disease-Specific Outcomes for Comparative Effectiveness Research Using ClinicalTrials.gov: Algorithm Development and Validation Study

Using big data to promote precision oral health in the context of a learning healthcare system

<p>Informatics Approaches for Harmonized Intelligent Integration of Stem Cell Research</p>

Collaborators (6)

Kensaku Kawamoto

Ramkiran Gouripeddi

Alejandro Domínguez Rodríguez

Guilherme Del Fiol

Anas Elghafari

Fatemeh Shah Mohammadi

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