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Cancer Research UK

20.240 Arbeiten6.689.377 Zitationen
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Relevante Arbeiten

Meistzitierte Publikationen im Bereich Gesundheit & MedTech

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Recent advances of HCI in decision-making tasks for optimized clinical workflows and precision medicine

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What is Interpretability?

Adrian Erasmus, T. D. P. Brunet, Eyal Fisher

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Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation

Michael Yeung, Leonardo Rundo, Nan Yang et al.

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Acting on incidental findings in research imaging

Joanna M. Wardlaw, H. Dele Davies, Thomas C. Booth et al.

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Challenges in ensuring the generalizability of image quantitation methods for MRI

Kathryn E. Keenan, Jana G. Delfino, Kalina V. Jordanova et al.

2021 · 40 Zit.

Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case

L. Escudero, Thomas Buddenkotte, Mohammad Al Sa’d et al.

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Leveraging large language models for structured information extraction from pathology reports

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2025 · 5 Zit.

HCI for biomedical decision-making: From diagnosis to therapy

Orazio Gambino, Leonardo Rundo, Roberto Pirrone et al.

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Letter to the Editor. Misconceptions in the field guide to big data for neurosurgeons

Michael T. C. Poon, Jorge Gaete-Villegas, Paul M. Brennan et al.

2021 · 1 Zit.

HTA10 HTA Considerations for Large Language Models in Healthcare

Charles E. Leonard, Harriet Unsworth, Sheryl Warttig et al.

2024 · 0 Zit.

TriDeNT : Triple deep network training for privileged knowledge distillation in histopathology

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2025 · 0 Zit.

Enabling digital multifactorial risk assessment in primary care: an umbrella review and recommendations for design and implementation

Lily C. Taylor, Niels Peek, Ari Ercole et al.

2026 · 0 Zit.

2619P How clinicians decide – analyzing real-world practice patterns in metastatic renal cell carcinoma (mRCC) with machine learning: Results from the international metastatic renal cell carcinoma database consortium (IMDC)

David Maj, D. O'Sullivan, Martín Zarbá et al.

2025 · 0 Zit.

S32 Clinical readiness of AI tumour volume quantification in mesothelioma: results of the meso-Q study

Joshua Roche, Akari Win Thu, A. MacPherson et al.

2025 · 0 Zit.