Linda Chu

Associate Professor

Johns Hopkins University School of Medicine

United States

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About

Dr. Linda Chu is an Associate Professor at Johns Hopkins Medicine in the United States. Her research focuses on advanced imaging techniques, AI applications in healthcare, and innovative approaches to diagnosis and treatment in oncology and infectious diseases. Recent publications include studies on sarcoidosis, tuberculosis, and the role of deep learning in early detection of pancreatic cancer.

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Collaborators (5)

Alison Klein

Professor

UNITED STATES

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Javad Azadi

UNITED STATES

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Renato Cuocolo

Associate Professor

University of Salerno

ITALY

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Jin He

Associate Professor

Johns Hopkins University School of Medicine

UNITED STATES

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Florent Tixier

Johns Hopkins University

UNITED STATES

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Linda Chu

Research Interests

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About

Articles (29)

Early Detection of Pancreatic Cancer on CT: Advancements with Deep Learning

Ensuring Reproducibility and Deploying Models with the Image2Radiomics Framework: An Evaluation of Image Processing on PanNET Model Performance

A Rare Case of Sarcoidosis presenting as a Lung Mass with Treatment Associated Mycobacterium marinum Infection of the Hand

Pott’s disease: A case of multilevel vertebral tuberculosis with spinal deformity

Balancing Model Generalization With Local Performance: Insights From AI in Prostate Cancer Classification

Identity Matters: The Potential for a Frictionless and Secure Patient Experience

Can Obsolescence Be Cured?

Reply

The Elevation Approach for Work-Life Harmony

AI in the Era of GPT: Transforming the Future of Work and Discovery

Amplifying Research in Radiology: The Podcast Effect

Cinematic rendering of primary adrenal lymphoma

Deep pelvic endometriosis causing ureteral obstruction

Leadership: A Different Approach from A Different Perspective

Performance of explainable artificial intelligence in guiding the management of patients with a pancreatic cyst

Radiomics machine learning algorithm facilitates detection of small pancreatic neuroendocrine tumors on CT

The Current State of Artificial Intelligence and Its Intersection With Radiology

An incidental large adrenal schwannoma: A case report

How Tech Can Help Us Improve Health Care While Still Putting Patients First

Assessment of RadiomIcS rEsearch (ARISE): a brief guide for authors, reviewers, and readers from the Scientific Editorial Board of European Radiology

Accurate non-invasive grading of nonfunctional pancreatic neuroendocrine tumors with a CT derived radiomics signature

A primer on artificial intelligence in pancreatic imaging

Addressing Mental Health in Professional Management

Building Bridges: Future-Proofing Established Industries and Building Relationships with the Black Community

Finding Common Ground: The Intersection of Science, Creativity, and the Human Connection

Imaging of Gastrointestinal Stromal Tumors: The Next Wave of Radiology

AI as Virtual Biopsy Tool to Predict Macrotrabecular-Massive Hepatocellular Carcinoma

Beyond chatting: The opportunities and challenges of ChatGPT in medicine and radiology

The Future of Work: Opportunities for Dynamic Growth

Collaborators (5)

Alison Klein

Javad Azadi

Renato Cuocolo

Jin He

Florent Tixier

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