Andre Dekker

Professor of Clinical Data Science

Maastricht University Medical Centre

Netherlands

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About

Professor Andre Dekker is a faculty member at Maastricht University Medical Centre, Netherlands. His research focuses on clinical data science, particularly in areas such as radiomics, cardiovascular disease risk prediction, and healthcare analytics. His recent work includes developing methodologies for sample size calculations in predictive modeling and advancing privacy-preserving techniques for health care analytics.

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Collaborators (17)

Iñigo Bermejo

University of Maastricht

NETHERLANDS

Andre Dekker

Research Interests

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About

Articles (20)

Minimum sample size calculation for radiomics-based binary outcome prediction models: Theoretical framework and practical example

Exploring safety of down‐titrating diuretics in heart failure management

Development and temporal evaluation of sex-specific models to predict 4-year atherosclerotic cardiovascular disease risk based on age and neighbourhood characteristics in South Limburg, the Netherlands

A Governance Framework for Federated Learning Projects in Healthcare

What to Report? A Systematic Review of Medical AI Reporting Guidelines: Preliminary Results

Data Interoperability in Context: The Importance of Open-Source Implementations When Choosing Open Standards

Developing an ICD-10 Coding Assistant: Pilot Study Using RoBERTa and GPT-4 for Term Extraction and Description-Based Code Selection

Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study

Prognostic modeling in head and neck cancer: deep learning or handcrafted radiomics?

An Overview of Real-World Data Infrastructure for Cancer Research

pCR and 2-Year Disease-Free Survival: A Combination of the Two Endpoints as a New Classification for Locally Advanced Rectal Cancer Patients—An Updated Pooled Analysis of Eleven International Randomized Trials

Applying federated learning to combat food fraud in food supply chains

Defining the role of real-world data in cancer clinical research: The position of the European Organisation for Research and Treatment of Cancer

Computed tomography and radiation dose images-based deep-learning model for predicting radiation pneumonitis in lung cancer patients after radiation therapy

How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation

Frequency-Domain-Based Structure Losses for CycleGAN-Based Cone-Beam Computed Tomography Translation

Identifying Confounders Using Bayesian Networks and Estimating Treatment Effect in Prostate Cancer With Observational Data

Clinician perspectives on clinical decision support systems in lung cancer: Implications for shared decision‐making

Clinical evaluation of automated segmentation for body composition analysis on abdominal L3 CT slices in polytrauma patients

Health Literacy and eHealth: Challenges and Strategies

Collaborators (17)

Iñigo Bermejo

Suraj Pai

Johan van Soest

Daniel Kapitan

Varsha Gouthamchand

Martijn Poeze

Katja Aben

Katie Spencer

Enrique Hortal

Yamine Bouzembrak

Hajar Hasannejadasl

Leonard Wee

Anshu Ankolekar

Stylianos Asteriadis

Joshi Hogenboom

Niels Peek

Cheryl Roumen

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