Joachim Krois
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View article: The Interplay Between Periodontitis, Caries and Dental Restorations in an Adult Population
The Interplay Between Periodontitis, Caries and Dental Restorations in an Adult Population Open
Aim To explore the local co‐occurrence patterns between caries and periodontal parameters (probing depth [PD] and clinical attachment loss [CAL]) and assess whether restorations/caries are spatially associated with poorer periodontal outco…
View article: Expert gaze as a usability indicator of medical AI decision support systems: a preliminary study
Expert gaze as a usability indicator of medical AI decision support systems: a preliminary study Open
Given the current state of medical artificial intelligence (AI) and perceptions towards it, collaborative systems are becoming the preferred choice for clinical workflows. This work aims to address expert interaction with medical AI suppor…
View article: Conquering class imbalances in deep learning-based segmentation of dental radiographs with different loss functions
Conquering class imbalances in deep learning-based segmentation of dental radiographs with different loss functions Open
In dental use cases it is often important to predict minority classes such as pathologies accurately. Using specific loss function may be an effective strategy to overcome data imbalance when training deep learning models.
View article: <scp>ACES</scp>: A new framework for the application of the 2018 periodontal status classification scheme to epidemiological survey data
<span>ACES</span>: A new framework for the application of the 2018 periodontal status classification scheme to epidemiological survey data Open
Aim To propose a framework for consistently applying the 2018 periodontal status classification scheme to epidemiological surveys (Application of the 2018 periodontal status Classification to Epidemiological Survey data, ACES). Proposed Fr…
View article: Machine Learning to Predict Apical Lesions: A Cross-Sectional and Model Development Study
Machine Learning to Predict Apical Lesions: A Cross-Sectional and Model Development Study Open
(1) Background: We aimed to identify factors associated with the presence of apical lesions (AL) in panoramic radiographs and to evaluate the predictive value of the identified factors. (2) Methodology: Panoramic radiographs from 1071 pati…
View article: Machine Learning to Predict Apical Lesions: A Cross-Sectional and Model Development Study
Machine Learning to Predict Apical Lesions: A Cross-Sectional and Model Development Study Open
(1) Background: We aimed to identify factors associated with the presence of apical lesions (AL) on panoramic radiographs and to evaluate the predictive value of the identified factors. (2) Methodology: Panoramic radiographs from 1071 pati…
View article: Impact of Noisy Labels on Dental Deep Learning—Calculus Detection on Bitewing Radiographs
Impact of Noisy Labels on Dental Deep Learning—Calculus Detection on Bitewing Radiographs Open
Supervised deep learning requires labelled data. On medical images, data is often labelled inconsistently (e.g., too large) with varying accuracies. We aimed to assess the impact of such label noise on dental calculus detection on bitewing…
View article: Identification of Dental Implant Systems Using a Large-Scale Multicenter Data Set
Identification of Dental Implant Systems Using a Large-Scale Multicenter Data Set Open
This study aimed to evaluate the efficacy of deep learning (DL) for the identification and classification of various types of dental implant systems (DISs) using a large-scale multicenter data set. We also compared the classification accur…
View article: Super-Resolution of Dental Panoramic Radiographs Using Deep Learning: A Pilot Study
Super-Resolution of Dental Panoramic Radiographs Using Deep Learning: A Pilot Study Open
Using super-resolution (SR) algorithms, an image with a low resolution can be converted into a high-quality image. Our objective was to compare deep learning-based SR models to a conventional approach for improving the resolution of dental…
View article: Machine Learning in Dentistry: A Scoping Review
Machine Learning in Dentistry: A Scoping Review Open
Machine learning (ML) is being increasingly employed in dental research and application. We aimed to systematically compile studies using ML in dentistry and assess their methodological quality, including the risk of bias and reporting sta…
View article: Monolithic hybrid abutment crowns (screw‐retained) versus monolithic hybrid abutments with adhesively cemented monolithic crowns
Monolithic hybrid abutment crowns (screw‐retained) versus monolithic hybrid abutments with adhesively cemented monolithic crowns Open
Objectives The objective of this study is to compare monolithic hybrid abutment crowns (screw‐retained) versus monolithic hybrid abutments with adhesively cemented monolithic single‐tooth crowns. Materials and Methods Twenty subjects in ne…
View article: Resin Infiltration of Non-Cavitated Proximal Caries Lesions in Primary and Permanent Teeth: A Systematic Review and Scenario Analysis of Randomized Controlled Trials
Resin Infiltration of Non-Cavitated Proximal Caries Lesions in Primary and Permanent Teeth: A Systematic Review and Scenario Analysis of Randomized Controlled Trials Open
The present study aimed to meta-analyze and evaluate the certainty of evidence for resin infiltration of proximal carious lesions in primary and permanent teeth. While resin infiltration has been shown efficacious for caries management, th…
View article: How Do Users Respond to Mass Vaccination Centers? A Cross-Sectional Study Using Natural Language Processing on Online Reviews to Explore User Experience and Satisfaction with COVID-19 Vaccination Centers
How Do Users Respond to Mass Vaccination Centers? A Cross-Sectional Study Using Natural Language Processing on Online Reviews to Explore User Experience and Satisfaction with COVID-19 Vaccination Centers Open
To reach large groups of vaccine recipients, several high-income countries introduced mass vaccination centers for COVID-19. Understanding user experiences of these novel structures can help optimize their design and increase patient satis…
View article: Developing Automated Computer Algorithms to Phenotype Periodontal Disease Diagnoses in Electronic Dental Records
Developing Automated Computer Algorithms to Phenotype Periodontal Disease Diagnoses in Electronic Dental Records Open
Objective Our objective was to phenotype periodontal disease (PD) diagnoses from three different sections (diagnosis codes, clinical notes, and periodontal charting) of the electronic dental records (EDR) by developing two automated comput…
View article: Evaluation of AI model for cephalometriclandmark classification (TG Dental)
Evaluation of AI model for cephalometriclandmark classification (TG Dental) Open
Purpose: The accuracy of cephalometric landmark identification for malocclusion classification is essential for the diagnosis and treatment planning. The identification of these landmarks is often complex and time consuming for the orthodo…
View article: Artificial Intelligence for Caries Detection: Value of Data and Information
Artificial Intelligence for Caries Detection: Value of Data and Information Open
If increasing practitioners’ diagnostic accuracy, medical artificial intelligence (AI) may lead to better treatment decisions at lower costs, while uncertainty remains around the resulting cost-effectiveness. In the present study, we asses…
View article: Emulating Clinical Diagnostic Reasoning for Jaw Cysts with Machine Learning
Emulating Clinical Diagnostic Reasoning for Jaw Cysts with Machine Learning Open
The detection and classification of cystic lesions of the jaw is of high clinical relevance and represents a topic of interest in medical artificial intelligence research. The human clinical diagnostic reasoning process uses contextual inf…
View article: A Survey on the Use of Artificial Intelligence by Clinicians in Dentistry and Oral and Maxillofacial Surgery
A Survey on the Use of Artificial Intelligence by Clinicians in Dentistry and Oral and Maxillofacial Surgery Open
Background: Applications of artificial intelligence (AI) in medicine and dentistry have been on the rise in recent years. In dental radiology, deep learning approaches have improved diagnostics, outperforming clinicians in accuracy and eff…
View article: Federated Learning in Dentistry: Chances and Challenges
Federated Learning in Dentistry: Chances and Challenges Open
Building performant and robust artificial intelligence (AI)–based applications for dentistry requires large and high-quality data sets, which usually reside in distributed data silos from multiple sources (e.g., different clinical institut…
View article: Towards Trustworthy AI in Dentistry
Towards Trustworthy AI in Dentistry Open
Medical and dental artificial intelligence (AI) require the trust of both users and recipients of the AI to enhance implementation, acceptability, reach, and maintenance. Standardization is one strategy to generate such trust, with quality…
View article: Hyperparameter Tuning and Automatic Image Augmentation for Deep Learning-Based Angle Classification on Intraoral Photographs—A Retrospective Study
Hyperparameter Tuning and Automatic Image Augmentation for Deep Learning-Based Angle Classification on Intraoral Photographs—A Retrospective Study Open
We aimed to assess the effects of hyperparameter tuning and automatic image augmentation for deep learning-based classification of orthodontic photographs along the Angle classes. Our dataset consisted of 605 images of Angle class I, 1038 …
View article: Benchmarking Deep Learning Models for Tooth Structure Segmentation
Benchmarking Deep Learning Models for Tooth Structure Segmentation Open
A wide range of deep learning (DL) architectures with varying depths are available, with developers usually choosing one or a few of them for their specific task in a nonsystematic way. Benchmarking (i.e., the systematic comparison of stat…
View article: Segmentation of Dental Restorations on Panoramic Radiographs Using Deep Learning
Segmentation of Dental Restorations on Panoramic Radiographs Using Deep Learning Open
Convolutional Neural Networks (CNNs) such as U-Net have been widely used for medical image segmentation. Dental restorations are prominent features of dental radiographs. Applying U-Net on the panoramic image is challenging, as the shape, …
View article: Self-Supervised Learning Methods for Label-Efficient Dental Caries Classification
Self-Supervised Learning Methods for Label-Efficient Dental Caries Classification Open
High annotation costs are a substantial bottleneck in applying deep learning architectures to clinically relevant use cases, substantiating the need for algorithms to learn from unlabeled data. In this work, we propose employing self-super…
View article: Evaluation of the Clinical, Technical, and Financial Aspects of Cost-Effectiveness Analysis of Artificial Intelligence in Medicine: Scoping Review and Framework of Analysis
Evaluation of the Clinical, Technical, and Financial Aspects of Cost-Effectiveness Analysis of Artificial Intelligence in Medicine: Scoping Review and Framework of Analysis Open
Background Cost-effectiveness analysis of artificial intelligence (AI) in medicine demands consideration of clinical, technical, and economic aspects to generate impactful research of a novel and highly versatile technology. Objective We a…