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James Hillis

Massachusetts General Hospital

United States

Research Interests

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Professors in United States Professors in Medical Imaging Medical Imaging professors in United States

Articles (16)

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2026

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2023

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2023

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2023

Collaborators (9)

Mootaz M. Salman

Senior Research Fellow (Faculty)

University of Oxford

UNITED KINGDOM

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Zoltan Molnar

Professor of Developmental Neuroscience

University of Oxford

UNITED KINGDOM

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Kerstin Noëlle Vokinger

Professor and Academic Chair for Regulation in Law, Medicine and Technology

University of Zurich

SWITZERLAND

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Jeffrey Blume

Associate Dean for Academic and Faculty Affairs, Professor of Data Science

University of Virginia

UNITED STATES

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Filipe Moura

Assistant Professor

Yale University

UNITED STATES

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Donnella Comeau

Neuroradiology Attending

Beth Israel Deaconess Medical Center

UNITED STATES

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Francis Szele

University of Oxford

UNITED KINGDOM

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Dhanu Gupta

Group Leader at University of Oxford

University of Oxford

GLOBAL

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Donald J MacIntyre

Honorary Reader

The University of Edinburgh

UNITED KINGDOM

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James Hillis

Research Interests

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Articles (16)

Natural language processing-driven knowledge graphs for transformative public health intelligence and research datasets in urgent and emergency care

Artificial intelligence in wearable seizure detection devices: current technologies and future directions

Evaluation of an artificial intelligence model for the identification of obstructive hydrocephalus on computed tomography of the head.

Artificial Intelligence-Enabled Devices in Neurology: Mapping the Present and Future

Galectin-3 induces neurodevelopmental apical-basal polarity and regulates gyrification

Evaluating the Performance and Clinical Utility of AI-driven Diagnostic Tools in Radiology

Detection of Hypertrophic Cardiomyopathy on Electrocardiogram Using Artificial Intelligence

Health AI needs meaningful human involvement: lessons from war

AI Devices in Neurology—Moving From Diagnosis to Prognosis

The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs

The lucent yet opaque challenge of regulating artificial intelligence in radiology

Evaluation of an Artificial Intelligence Model for Identification of Intracranial Hemorrhage Subtypes on Computed Tomography of the Head

Evaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the Head

Head CT deep learning model is highly accurate for early infarct estimation

Addressing the Challenges of Implementing Artificial Intelligence Tools in Clinical Practice: Principles From Experience.

Auto-Detection of Motion Artifacts on CT Pulmonary Angiograms with a Physician-Trained AI Algorithm.

Collaborators (9)

Mootaz M. Salman

Zoltan Molnar

Kerstin Noëlle Vokinger

Jeffrey Blume

Filipe Moura

Donnella Comeau

Francis Szele

Dhanu Gupta

Donald J MacIntyre

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