Carlijn van der Aalst

Associate Professor

Erasmus MC

Netherlands

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About

Dr. Carlijn van der Aalst is an Associate Professor at Erasmus MC in the Netherlands. Her research focuses on artificial intelligence applications in lung cancer screening, examining considerations for AI integration in public health settings. Recent articles highlight her work on the feasibility of AI as a first reader in lung cancer trials and the implications of comprehensive CT screening for early detection.

Articles (10)

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2025

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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

Collaborators (3)

Harry de Koning

Erasmus University Rotterdam

NETHERLANDS

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Daiwei Han

NETHERLANDS

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John Field

Clinical Professor of Molecular Oncology

UNITED KINGDOM

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Carlijn van der Aalst

Research Interests

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Articles (10)

AI integrations with lung cancer screening: Considerations in developing AI in a public health setting.

Corrigendum to: Feasibility of AI as first reader in the 4-IN-THE-LUNG-RUN lung cancer screening trial: Impact on negative-misclassifications and clinical referral rate (European Journal of Cancer (2025) 216, 115214 (S0959804924018215), (10.1016/j.ejca.2024.115214))

Feasibility of AI as first reader in the 4-IN-THE-LUNG-RUN lung cancer screening trial: impact on negative-misclassifications and clinical referral rate

Paradigm shift in early detection: Lung cancer screening to comprehensive CT screening

Stage- and histology-specific sensitivity for the detection of lung cancer of the NELSON screening protocol—A modeling study

Short-term impact of cardiovascular screening by traditional risk assessment or coronary artery calcium score on health-related quality of life: the ROBINSCA trial

Medical costs of lung cancer by stage, histology and first-line treatment modality in the Netherlands (2012–2021)

Projected effectiveness of lung cancer screening and concurrent smoking cessation support in the Netherlands

Coronary Artery Calcium Scores After Prophylactic Premenopausal Bilateral Salpingo-Oophorectomy

Lung cancer volume doubling time by computed tomography: A systematic review and meta-analysis

Collaborators (3)

Harry de Koning

Daiwei Han

John Field

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