Wetenschappelijke publicaties per discipline
Algemeen
- Babu Payedimarri et al. 2021 (Int J Environ Res Public Health) Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review
- Horgan et al. 2020 (Biomed Hub) Propelling Health Care into the Twenties
- Van Calster et al. 2019 (J Am Med Inform Assoc) Predictive analytics in health care: how can we know it works?
Beeldvorming
- Lambrechts et al. 2022 (Front Robot AI) Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty
Endocrinologie
- Perkins et al. 2021 (Science) Type 1 diabetes glycemic management: Insulin therapy, glucose monitoring, and automation
Fysische geneeskunde en revalidatie
- De Laet et al. 2017 (PLoS One) Does expert knowledge improve automatic probabilistic classification of gait joint motion patterns in children with cerebral palsy?
Gynaecologie en verloskunde
- Izci et al. 2020 (JNCI) A Systematic Review of Estimating Breast Cancer Recurrence at the Population-Level with Administrative Data
- Vasconcelos et al. 2018 (Int J Comput Assist Radiol Surg) Towards computer-assisted TTTS: Laser ablation detection for workflow segmentation from fetoscopic video
- Van Hoorde et al. 2015 (J Biomed Inform) A spline-based tool to assess and visualize the calibration of multiclass risk predictions
- Daemen et al. 2012 (Artif Intell Med) Improved modeling of clinical data with kernel methods
Hart- en vaatziekten
- Wei et al. 2022 (ESC Heart Fail) The novel proteomic signature for cardiac allograft vasculopathy
- Attia et al. 2021 (Mayo Clin Proc) Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram
- Gallard et al. 2021 (Int J Cardiovasc Imaging) Prediction of response to cardiac resynchronization therapy using a multi-feature learning method
- Van den Eynde et al. 2021 (Front Cardiovasc Med) Medicine-Based Evidence in Congenital Heart Disease: How Artificial Intelligence Can Guide Treatment Decisions for Individual Patients
- Hermans et al. 2020 (Heart Rhythm) Improving long QT syndrome diagnosis by a polynomial-based T-wave morphology characterization
- Sengupta et al. 2020 (JACC Cardiovasc Imaging) Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist: Reviewed by the American College of Cardiology Healthcare Innovation Council
- Goovaerts et al. 2018 (IEEE J Biomed Health Inform) A Machine Learning Approach for Detection and Quantification of QRS Fragmentation
- Mada et al. 2016 (J Am Soc Echocardiogr) New Automatic Tools to Identify Responders to Cardiac Resynchronization Therapy
Intensieve geneeskunde
- Carra et al. 2020 (J Crit Care) Data-driven ICU management: Using Big Data and algorithms to improve outcomes
- Flechet et al. 2019 (Crit Care) Machine learning versus physicians’ prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor (zie ook www.akipredictor.com)
- Bailly et al. 2018 (Intensive Care Med) What's new in ICU in 2050: big data and machine learning
- Janssens et al. 2013 (Medical Image Analysis) Charisma: An integrated approach to automatic H&E-stained skeletal muscle cell segmentation using supervised learning and novel robust clump splitting
- Meyfroidt et al. 2009 (Best Pract Res Clin Anaesthesiol) Machine learning techniques to examine large patient databases
Kindergeneeskunde
- Luca et al. 2014 (Artif Intell Med) Detecting rare events using extreme value statistics applied to epileptic convulsions in children
Laboratoriumgeneeskunde
- Hulsen et al. 2022 (Clin Chem Lab Med) From big data to better patient outcomes
- Prodan Zitnik et al. 2018 (Clin Chem Lab Med) Personalized laboratory medicine: a patient-centered future approach
Maag-, darm- en leverziekten
- Gui et al. 2022 (Gut) PICaSSO Histologic Remission Index (PHRI) in ulcerative colitis: development of a novel simplified histological score for monitoring mucosal healing and predicting clinical outcomes and its applicability in an artificial intelligence system
- Iacucci et al. 2022 (Endoscopy) A virtual chromoendoscopy artificial intelligence system to detect endoscopic and histologic activity/remission and predict clinical outcomes in ulcerative colitis
- Schmitz et al. 2022 (Gut) Artificial intelligence in GI endoscopy: stumbling blocks, gold standards and the role of endoscopy societies
- Ahmad et al. 2021 (Endoscopy) Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method
- Eelbode et al. 2021 (Best Pract Res Clin Gastroenterol) Pitfalls in training and validation of deep learning systems
- Everson et al. 2021 (Gastrointest Endosc) A clinically interpretable convolutional neural network for the real-time prediction of early squamous cell cancer of the esophagus: comparing diagnostic performance with a panel of expert European and Asian endoscopists
- Sarrabayrouse et al. 2021 (mSystems) Fungal and Bacterial Loads: Noninvasive Inflammatory Bowel Disease Biomarkers for the Clinical Setting
- Sinonquel et al. 2021 (Dig Endosc) Artificial intelligence and its impact on quality improvement in upper and lower gastrointestinal endoscopy
- Sinonquel et al. 2021 (Best Pract Res Clin Gastroenterol) Striving for quality improvement: can artificial intelligence help?
- Sudhakar et al. 2021 (Front Microbiol) Computational Biology and Machine Learning Approaches to Understand Mechanistic Microbiome-Host Interactions
- Bossuyt et al. 2020 (Gastroenterology) Assessing Disease Activity in Ulcerative Colitis Using Artificial Intelligence: Can "Equally Good" Be Seen as "Better"?
- Bossuyt et al. 2020 (Gut) Automatic, computer-aided determination of endoscopic and histological inflammation in patients with mild to moderate ulcerative colitis based on red density
- de Groof et al. 2020 (Gastroenterology) Deep-Learning System Detects Neoplasia in Patients With Barrett's Esophagus With Higher Accuracy Than Endoscopists in a Multistep Training and Validation Study With Benchmarking
- Dercle et al. 2020 (J Natl Cancer Inst) Radiomics Response Signature for Identification of Metastatic Colorectal Cancer Sensitive to Therapies Targeting EGFR Pathway
- Seyed Tabib et al. 2020 (Gut) Big data in IBD: big progress for clinical practice
- Bisschops et al. 2019 (Endoscopy) Advanced imaging for detection and differentiation of colorectal neoplasia: European Society of Gastrointestinal Endoscopy (ESGE) Guideline - Update 2019
- Neumann et al. 2019 (Dig Endosc) Artificial intelligence and the future of endoscopy
- De Groof et al. 2019 (United European Gastroenterol J) The Argos project: The development of a computer-aided detection system to improve detection of Barrett's neoplasia on white light endoscopy
- Sehgal et al. 2018 (Gastroenterol Res Pract) Machine Learning Creates a Simple Endoscopic Classification System that Improves Dysplasia Detection in Barrett's Oesophagus amongst Non-expert Endoscopists
- Cuypers et al. 2017 (Infect Genet Evol) Exploring resistance pathways for first-generation NS3/4A protease inhibitors boceprevir and telaprevir using Bayesian network learning
- Van der Sommen et al. 2016 (Endoscopy) Computer-aided detection of early neoplastic lesions in Barrett's esophagus
Mond-, kaak- en aangezichtschirurgie
- Mureșanu et al. 2023 (Oral Radiol) Artificial intelligence models for clinical usage in dentistry with a focus on dentomaxillofacial CBCT: a systematic review
- Baseri Saadi et al. 2022 (Bone Rep) Convolutional neural network for automated classification of osteonecrosis and related mandibular trabecular patterns
- Cavalcante Fontenele et al. 2022 (J Dent) Influence of dental fillings and tooth type on the performance of a novel artificial intelligence-driven tool for automatic tooth segmentation on CBCT images - A validation study
- Shujaat et al. 2022 (Clin Oral Investig) Synergy between artificial intelligence and precision medicine for computer-assisted oral and maxillofacial surgical planning
- Ferreira Leite et al. 2021 (Clin Oral Investig) Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographs
- Lahoud et al. 2021 (J Endod) Artificial Intelligence for Fast and Accurate 3-Dimensional Tooth Segmentation on Cone-beam Computed Tomography
- Orhan et al. 2021 (Biomed Res Int) Development and Validation of a Magnetic Resonance Imaging-Based Machine Learning Model for TMJ Pathologies
- Verhelst et al. 2021 (J Dent) Layered deep learning for automatic mandibular segmentation in cone-beam computed tomography
- Ferreira Leite et al. 2020 (Proteomics Clin Appl) Radiomics and Machine Learning in Oral Healthcare
- Vranckx et al. 2020 (Int J Environ Res Public Health) Artificial Intelligence (AI)-Driven Molar Angulation Measurements to Predict Third Molar Eruption on Panoramic Radiographs
Nefrologie
- Cippa et al. 2018 (JCI Insight) Transcriptional trajectories of human kidney injury progression
Neonatologie
- Ansari et al. 2016 (Clin Neurophysiol) Improved multi-stage neonatal seizure detection using a heuristic classifier and a data-driven post-processor
Neurochirurgie
- Smeijers & Depreitere 2021 (Eur Spine J) Prognostic scores for survival as decisional support for surgery in spinal metastases: a performance assessment systematic review
Neurologie
- Etminani et al. 2022 (Eur J Nucl Med Mol Imaging) A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET
- Hens et al. 2022 (J Peripher Nerv Syst) Validation of an Artificial Intelligence driven framework to automatically detect red flag symptoms in screening for rare diseases in electronic health records: hereditary transthyretin amyloidosis polyneuropathy as a key example
- McCarthy et al. 2022 (Hum Brain Mapp) Data-driven staging of genetic frontotemporal dementia using multi-modal MRI
- Bretzner et al. 2021 (Front Neurosci) MRI Radiomic Signature of White Matter Hyperintensities Is Associated With Clinical Phenotypes
- Young et al. 2021 (Neurology) Characterizing the Clinical Features and Atrophy Patterns of MAPT-Related Frontotemporal Dementia With Disease Progression Modeling
- Schirmer et al. 2019 (Neuroimage Clin) White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts - The MRI-GENIE study
- Wu et al. 2019 (Stroke) Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
- Ten Kate et al. 2018 (Alzheimers Res Ther) MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study
- Bruffaerts 2018 (J Neurol) Machine learning in neurology: what neurologists can learn from machines and vice versa
- Grube et al. 2016 (Brain) Core auditory processing deficits in primary progressive aphasia
Neus-, keel- en oorziekten, gelaats- en halschirurgie
- Cavalieri et al. 2020 (Eur J Cancer) Prognostic nomogram in patients with metastatic adenoid cystic carcinoma of the salivary glands
Nucleaire geneeskunde
- Schramm et al. 2021 (Neuroimage) Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network
Oogziekten
- Andrade De Jesus et al. 2020 (Transl Vis Sci Technol) OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma
- Barbosa Breda et al. 2020 (Prog Brain Res) Advanced vascular examinations of the retina and optic nerve head in glaucoma
- Barbosa Breda et al. 2020 (Exp Eye Res) Metabolomic profiling of aqueous humor from glaucoma patients - The metabolomics in surgical ophthalmological patients (MISO) study
- Lemmens et al. 2020 (Alzheimers Res Ther) Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer's disease patients
- Tan et al. 2020 (Curr Opin Ophthalmol) Glaucoma screening: where are we and where do we need to go?
- Hemelings et al. 2019 (Acta Ophthalmol) Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning
- Orlando et al. 2017 (Med Phys) Proliferative diabetic retinopathy characterization based on fractal features: Evaluation on a publicly available dataset
Pathologische ontleedkunde
- Abate et al. 2015 (Leukemia) A novel patient-derived tumorgraft model with TRAF1-ALK anaplastic large-cell lymphoma translocation
Pneumologie
- Gonem et al. 2020 (Thorax) Applications of artificial intelligence and machine learning in respiratory medicine
- Topalovic et al. 2019 (Eur Respir J) Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests
- Topalovic et al. 2017 (Respiration) Automated Interpretation of Pulmonary Function Tests in Adults with Respiratory Complaints
Radiologie
- Haller et al. 2022 (Neuroradiology) The R-AI-DIOLOGY checklist: a practical checklist for evaluation of artificial intelligence tools in clinical neuroradiology
- Biebau et al. 2021 (J Belg Soc Radiol) Comparing Visual Scoring of Lung Injury with a Quantifying AI-Based Scoring in Patients with COVID-19
- Huisman et al. 2021 (Eur Radiol) An international survey on AI in radiology in 1,041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude
- Huisman et al. 2021 (Eur Radiol) An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education
- Rodriguez Perez et al. 2021 (J Med Imaging) Methodology to create 3D models of COVID-19 pathologies for virtual clinical trials
- Jain et al. 2019 (J Neurotrauma) Automatic Quantification of Computed Tomography Features in Acute Traumatic Brain Injury
- Kiss et al. 2006 (Acad Radiol) Computer-aided detection of colonic polyps using low-dose CT acquisitions
Radiotherapie-oncologie
- Ng et al. 2022 (Cancers) Current Radiotherapy Considerations for Nasopharyngeal Carcinoma
- Zanca et al. 2021 (Phys Med) Focus issue: Artificial intelligence in medical physics
- Zanca et al. 2021 (Phys Med) Expanding the medical physicist curricular and professional programme to include Artificial Intelligence
- Brouwer et al. 2020 (Phys Imaging Radiat Oncol) Machine learning applications in radiation oncology: Current use and needs to support clinical implementation
- Vandewinckele et al. 2020 (Radiother Oncol) Overview of artificial intelligence-based applications in radiotherapy: Recommendations for implementation and quality assurance
- Van der Veen et al. 2019 (Radiother Oncol) Benefits of deep learning for delineation of organs at risk in head and neck cancer
Reumatologie
- Soret et al. 2021 (Nat Commun) A new molecular classification to drive precision treatment strategies in primary Sjögren's syndrome
- Van Nieuwenhove et al. 2019 (Ann Rheum Dis) Machine learning identifies an immunological pattern associated with multiple juvenile idiopathic arthritis subtypes
Tandheelkunde
- De Tobel et al. 2017 (J Forensic Odontostomatol) An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study
Thoraxheelkunde
- Rice et al. 2017 (Ann Surg) Esophageal Cancer: Associations With (pN+) Lymph Node Metastases
Urgentiegeneeskunde
- Longrois et al. 2019 (Eur J Trauma Emerg Surg) Streamlining pre- and intra-hospital care for patients with severe trauma: a white paper from the European Critical Care Foundation
Urologie
- Roussel et al. 2022 (Eur Urol) Novel Imaging Methods for Renal Mass Characterization: A Collaborative Review
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