Innovating dental diagnostics: ChatGPT's accuracy on diagnostic challenges.

INTRODUCTION: Complex patient diagnoses in dentistry require a multifaceted approach which combines interpretations of clinical observations with an in-depth understanding of patient history and presenting problems. The present study aims to elucidate the implications of ChatGPT (OpenAI) as a comprehensive diagnostic tool in the dental clinic through examining the chatbot's diagnostic performance on challenging patient cases retrieved from the literature. METHODS: Our study subjected ChatGPT3.5 and ChatGPT4 to descriptions of patient cases for diagnostic challenges retrieved from the literature. Sample means were compared using a two-tailed t-test, while sample proportions were compared using a two-tailed χ2 test. A p-value below the threshold of 0.05 was deemed statistically significant. RESULTS: When prompted to generate their own differential diagnoses, ChatGPT3.5 and ChatGPT4 achieved a diagnostic accuracy of 40% and 62%, respectively. When basing their diagnostic processes on a differential diagnosis retrieved from the literature, ChatGPT3.5 and ChatGPT4 achieved a diagnostic accuracy of 70% and 80%, respectively. CONCLUSION: ChatGPT displays an impressive capacity to correctly diagnose complex diagnostic challenges in the field of dentistry. Our study paints a promising potential for the chatbot to 1 day serve as a comprehensive diagnostic tool in the dental clinic.

A Descriptive Diagnosis or a Causal Explanation? Accuracy of Depictions of Depression on Authoritative Health Organization Websites.

INTRODUCTION: Psychiatric diagnoses are descriptive in nature, but the lay public commonly misconceives them as causal explanations. It is not known whether this logical error, a form of circular reasoning, can sometimes be mistakenly reinforced by health authorities themselves. In this study, we investigated the prevalence of misleading causal descriptions of depression in the information provided by authoritative mental health organizations on widely accessed internet sites. METHODS: We searched for popular websites managed by leading mental health organizations and conducted a content analysis to evaluate whether they presented depression accurately as a description of symptoms, or inaccurately as a causal explanation. RESULTS: Most websites used language that inaccurately described depression as a causal explanation to depressive symptoms. CONCLUSION: Leading professional medical and psychiatric organizations commonly confound depression, a descriptive diagnostic label, with a causal explanation on their most prominently accessed informational websites. We argue that the scientifically inaccurate causal language in depictions of psychiatric diagnoses is potentially harmful because it leads the public to misunderstand the nature of mental health problems. Mental health authorities providing psychoeducation should clearly state that psychiatric diagnoses are purely descriptive to avoid misleading the public.

Microrobotics in endodontics: A perspective.

Microorganisms are the primary aetiological factor of apical periodontitis. The goal of endodontic treatment is to prevent and eliminate the infection by removing the microorganisms. However, microbial biofilms and the complex root canal anatomy impair the disinfection process. Effective and precise endodontic therapy could potentially be achieved using advanced multifunctional technologies that have the ability to access hard-to-reach surfaces and perform simultaneous biofilm killing, removal, and detection of microorganisms. Advances in microrobotics are providing novel therapeutic and diagnostic opportunities with high precision and efficacy to address current biofilm-related challenges in biomedicine. Concurrently, multifunctional magnetic microrobots have been developed to overcome the disinfection challenges of current approaches to disrupt, kill, and retrieve biofilms with the goal of enhancing the efficacy and precision of endodontic therapy. This article reviews the recent advances of microrobotics in healthcare and particularly advances to overcome disinfection challenges in endodontics, and provides perspectives for future research in the field.

Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.

OBJECTIVES: Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition which are challenging tasks for most clinicians. Recent research used machine learning (ML) algorithms to diagnose TMDs intelligently. This study aimed to systematically evaluate the quality of these studies and assess the diagnostic accuracy of existing models. MATERIALS AND METHODS: Twelve databases (Europe PMC, Embase, etc.) and two registers were searched for published and unpublished studies using ML algorithms on medical images. Two reviewers extracted the characteristics of studies and assessed the methodological quality using the QUADAS-2 tool independently. RESULTS: A total of 28 studies (29 reports) were included: one was at unclear risk of bias and the others were at high risk. Thus the certainty of evidence was quite low. These studies used many types of algorithms including 8 machine learning models (logistic regression, support vector machine, random forest, etc.) and 15 deep learning models (Resnet152, Yolo v5, Inception V3, etc.). The diagnostic accuracy of a few models was relatively satisfactory. The pooled sensitivity and specificity were 0.745 (0.660-0.814) and 0.770 (0.700-0.828) in random forest, 0.765 (0.686-0.829) and 0.766 (0.688-0.830) in XGBoost, and 0.781 (0.704-0.843) and 0.781 (0.704-0.843) in LightGBM. CONCLUSIONS: Most studies had high risks of bias in Patient Selection and Index Test. Some algorithms are relatively satisfactory and might be promising in intelligent diagnosis. Overall, more high-quality studies and more types of algorithms should be conducted in the future. CLINICAL RELEVANCE: We evaluated the diagnostic accuracy of the existing models and provided clinicians with much advice about the selection of algorithms. This study stated the promising orientation of future research, and we believe it will promote the intelligent diagnosis of TMDs.

Comparative Study of Fuzzy Rule-Based Classifiers for Medical Applications.

The use of machine learning in medical decision support systems can improve diagnostic accuracy and objectivity for clinical experts. In this study, we conducted a comparison of 16 different fuzzy rule-based algorithms applied to 12 medical datasets and real-world data. The results of this comparison showed that the best performing algorithms in terms of average results of Matthews correlation coefficient (MCC), area under the curve (AUC), and accuracy (ACC) was a classifier based on fuzzy logic and gene expression programming (GPR), repeated incremental pruning to produce error reduction (Ripper), and ordered incremental genetic algorithm (OIGA), respectively. We also analyzed the number and size of the rules generated by each algorithm and provided examples to objectively evaluate the utility of each algorithm in clinical decision support. The shortest and most interpretable rules were generated by 1R, GPR, and C45Rules-C. Our research suggests that GPR is capable of generating concise and interpretable rules while maintaining good classification performance, and it may be a valuable algorithm for generating rules from medical data.

Metal-Organic Framework (MOF)-A Universal Material for Biomedicine.

Metal-organic frameworks (MOFs) are a very promising platform for applications in various industries. In recent years, a variety of methods have been developed for the preparation and modification of MOFs, providing a wide range of materials for different applications in life science. Despite the wide range of different MOFs in terms of properties/sizes/chemical nature, they have not found wide application in biomedical practices at present. In this review, we look at the main methods for the preparation of MOFs that can ensure biomedical applications. In addition, we also review the available options for tuning the key parameters, such as size, morphology, and porosity, which are crucial for the use of MOFs in biomedical systems. This review also analyses possible applications for MOFs of different natures. Their high porosity allows the use of MOFs as universal carriers for different therapeutic molecules in the human body. The wide range of chemical species involved in the synthesis of MOFs makes it possible to enhance targeting and prolongation, as well as to create delivery systems that are sensitive to various factors. In addition, we also highlight how injectable, oral, and even ocular delivery systems based on MOFs can be used. The possibility of using MOFs as therapeutic agents and sensitizers in photodynamic, photothermal, and sonodynamic therapy was also reviewed. MOFs have demonstrated high selectivity in various diagnostic systems, making them promising for future applications. The present review aims to systematize the main ways of modifying MOFs, as well as the biomedical applications of various systems based on MOFs.

At the Core of Depression: A Diagnostic Interview of the Core Features of Depression.

INTRODUCTION: Valid and reliable methods for diagnosing depression are essential. The present study aimed to test the performance of a new diagnostic interview for depression focusing on the core symptoms of depression. METHOD: We developed a diagnostic interview for depression: the CORE Diagnostic Interview, CORE-DI, which assesses each of the core features of depression on the four dimensions: quality, reactivity, globality, and fluctuations over time. The diagnostic performance of this interview was tested in a clinical study including 83 individuals presenting with various depressive symptoms, who were interviewed independently (1) by means of the CORE-DI and the Mini-International Neuropsychiatric Interview (M.I.N.I.), and (2) by highly skilled specialists in depression representing gold standard diagnoses. RESULTS: We compared the outcome of the CORE-DI, the M.I.N.I., and the diagnosis made by clinicians, respectively, versus the gold standard diagnosis, using diagnostic efficiency statistics. The CORE-DI diagnosed depression with a high specificity (0.91, 95% CI: 0.85-0.97, for International Classification of Diseases [ICD]-10 criteria and 0.88, 95% CI: 0.81-0.95, for Diagnostic and Statistical Manual of Mental Disorders [DSM-5] criteria) compared to both M.I.N.I (specificity 0.44, 95% CI: 0.33-0.55) and clinical diagnoses (specificity 0.76, 95% CI: 0.67-0.85). The sensitivity of the CORE-DI was 0.61 (95% CI: 0.55-0.72) for ICD-10 criteria and 0.67 (95% CI: 0.57-0.77) for DSM-5 criteria. DISCUSSION/CONCLUSION: The CORE-DI increased the specificity of the depression diagnosis substantially compared to clinical diagnoses and the diagnoses obtained by M.I.N.I. The results point to the usefulness of an elaborated and systematic assessment of the core symptoms in the examination of patients with depressive symptoms and thereby indicate a way for further development of specific diagnostic tools for depression in both clinical and research settings. However, it should be noted that the sensitivity of the CORE-DI was modest, and the psychometric properties of the CORE-DI might be different in other settings with higher or lower prevalence or severity of depressive symptoms.

Conceptual Issues in Acute and Transient Psychotic Disorders.

Short-lived psychotic disorders as currently listed under "acute and transient psychotic disorder," ICD-11 Classification of Mental, Behavioural, and Neurodevelopmental Disorders, and "brief psychotic disorder," Diagnostic and Statistical Manual of Mental Disorders (DSM-5), constitute a point of divergence in the classification of psychotic disorders between the 2 diagnostic systems, which reveals the lack of knowledge about these conditions. Whether this is due to conceptual shortcomings inherent to the categories themselves and which spill over onto research or reflects a mismatch between the diagnostic criteria used and research techniques needs clarification. This study aimed to examine conceptual issues involved in the development of the above categories and shows that little continuity exists between earlier nosological concepts such as bouffée délirante, cycloid psychosis, and reactive psychosis and modern descriptive categories used to classify short-lived psychotic disorders. It seems likely that shortcomings in terms of symptom completeness, specificity, and heterogeneity, in addition to changes in definition and diagnostic criteria in successive DSM and ICD versions, have hampered empirical research, making it difficult to enhance the understanding of these conditions and achieve a closer concordance between the 2 classificatory systems.

A Comparative Study on a Novel Quality Assessment Protocol Based on Image Analysis Methods for Color Doppler Ultrasound Diagnostic Systems.

Color Doppler (CD) imaging is widely used in diagnostics since it allows real-time detection and display of blood flow superimposed on the B-mode image. Nevertheless, to date, a shared worldwide standard on Doppler equipment testing is still lacking. In this context, the study herein proposed would give a contribution focusing on the combination of five test parameters to be included in a novel Quality Assessment (QA) protocol for CD systems testing. A first approach involving the use of the Kiviat diagram was investigated, assuming the diagram area, normalized with respect to one of the gold standards, as an index of the overall Doppler system performance. The QA parameters were obtained from the post-processing of CD data through the implementation of custom-written image analysis methods and procedures, here applied to three brand-new high-technology-level ultrasound systems. Experimental data were collected through phased and convex array probes, in two configuration settings, by means of a Doppler flow phantom set at different flow rate regimes. The outcomes confirmed that the Kiviat diagram might be a promising tool applied to quality controls of Doppler equipment, although further investigations should be performed to assess the sensitivity and specificity of the proposed approach.

Alternative Diagnostic Models of the Psychotic Disorders: Evidence-Based Choices.

Standard diagnostic systems, the predominantly categorical DSM-5 and ICD-11, have limitations in validity, utility, and predictive and descriptive power. For psychotic disorders, these issues were partly addressed in current versions, but additional modifications are thought to be needed. Changes should be evidence based. We reviewed categorical, modified-categorical, and continuum-based models versus factor-based models of psychosis. Factors are clusters of symptoms or single prominent aspects of illness. Consistent evidence from studies of the genetics, pathobiology, and clinical presentation of psychotic disorders all support an underlying structure of factors, not categories, as best characterizing psychoses. Factors are not only the best fit but also comprehensive, as they can encompass any key feature of illness, including symptoms and course, as well as determinants of risk or response. Factors are inherently dimensional, even multidimensional, as are the psychoses themselves, and they provide the detail needed for either grouping or distinguishing patients for treatment decisions. The tools for making factor-based diagnoses are available, reliable, and concordant with actual practices used for clinical assessments. If needed, factors can be employed to create categories similar to those in current use. In addition, they can be used to define unique groupings of patients relevant to specific treatments or studies of the psychoses. Lastly, factor-based classifications are concordant with other comprehensive approaches to psychiatric nosology, including personalized (precision treatment) models and hierarchical models, both of which are currently being explored. Factors might be considered as the right primary structural choice for future versions of standard diagnostic systems, both DSM and ICD.

Posture Assessment in Dentistry for Different Visual Aids Using 2D Markers.

Attention and awareness towards musculoskeletal disorders (MSDs) in the dental profession has increased considerably in the last few years. From recent literature reviews, it appears that the prevalence of MSDs in dentists concerns between 64 and 93%. In our clinical trial, we have assessed the dentist posture during the extraction of 90 third lower molars depending on whether the operator performs the intervention by the use of the operating microscope, surgical loupes, or with the naked eye. In particular, we analyzed the evolution of the body posture during different interventions evaluating the impact of visual aids with respect to naked eye interventions. The presented posture assessment approach is based on 3D acquisitions of the upper body, based on planar markers, which allows us to discriminate spatial displacements up to 2 mm in translation and 1 degree in rotation. We found a significant reduction of neck bending in interventions using visual aids, in particular for those performed with the microscope. We further investigated the impact of different postures on MSD risk using a widely adopted evaluation tool for ergonomic investigations of workplaces, named (RULA) Rapid Upper Limb Assessment. The analysis performed in this clinical trial is based on a 3D marker tracker that is able to follow a surgeon's upper limbs during interventions. The method highlighted pros and cons of different approaches.

Pulp Vitality Testing with a Developed Universal Pulse Oximeter Probe Holder.

Background and Objectives An accurate determination of the pulp status is relevant for a proper endodontic diagnosis. Objectives: The aim was to develop a universal pulse oximeter probe holder for measuring the oxygen saturation and to evaluate the use of pulse oximetry as a test for pulp vitality, by comparing the levels of oxygen saturation in the index finger and in the healthy dental pulp. Materials and Methods The universal holder was designed with software and printed with a 3D printer. The study was carried out on 128 healthy teeth. They were divided into eight groups according to tooth type. Ten root canal treated teeth served as a negative control group. For each patient, a pulse oximeter was first applied on the tooth followed by the index finger. The significance level (α) was set at 0.05. Results: The developed and manufactured universal pulse oximeter probe holder was suitable to measure the pulp vitality of all types of teeth. The handle allowed for holding the pulse oximeter on the tooth in parallel, firmly and securely. Significantly higher oxygen saturation was observed in the index finger (97.22%) compared to the dental pulp (93.17%) (p < 0.001). No correlation was observed between the maxillary teeth and index finger oxygen saturation values (r = 0.05, p = 0.72), whereas, between the mandibular teeth and index finger, a positive correlation was detected (r = 0.29, p = 0.02). There were no significant differences in the pulp oxygen saturation values between different teeth groups. Conclusion: The newly developed universal pulse oximeter probe holder is an effective device for pulp vitality testing.

Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design.

BACKGROUND: Three-dimensional scans are increasingly used to quantify biological topographical changes and clinical health outcomes. Traditionally, the use of 3D scans has been limited to specialized centers owing to the high cost of the scanning equipment and the necessity for complex analysis software. Technological advances have made cheaper, more accessible methods of data capture and analysis available in the field of dentistry, potentially facilitating a primary care system to quantify disease progression. However, this system has yet to be compared with previous high-precision methods in university hospital settings. OBJECTIVE: The aim of this study was to compare a dental primary care method of data capture (intraoral scanner) with a precision hospital-based method (laser profilometer) in addition to comparing open source and commercial software available for data analysis. METHODS: Longitudinal dental wear data from 30 patients were analyzed using a two-factor factorial experimental design. Bimaxillary intraoral digital scans (TrueDefinition, 3M, UK) and conventional silicone impressions, poured in type-4 dental stone, were made at both baseline and follow-up appointments (mean 36 months, SD 10.9). Stone models were scanned using precision laser profilometry (Taicaan, Southampton, UK). Three-dimensional changes in both forms of digital scans of the first molars (n=76) were quantitatively analyzed using the engineering software Geomagic Control (3D Systems, Germany) and freeware WearCompare (Leeds Digital Dentistry, UK). Volume change (mm3) was the primary measurement outcome. The maximum point loss (µm) and the average profile loss (µm) were also recorded. Data were paired and skewed, and were therefore compared using Wilcoxon signed-rank tests with Bonferroni correction. RESULTS: The median (IQR) volume change for Geomagic using profilometry and using the intraoral scan was -0.37 mm3 (-3.75-2.30) and +0.51 mm3 (-2.17-4.26), respectively (P<.001). Using WearCompare, the median (IQR) volume change for profilometry and intraoral scanning was -1.21 mm3 (-3.48-0.56) and -0.39 mm3 (-3.96-2.76), respectively (P=.04). WearCompare detected significantly greater volume loss than Geomagic regardless of scanner type. No differences were observed between groups with respect to the maximum point loss or average profile loss. CONCLUSIONS: As expected, the method of data capture, software used, and measurement metric all significantly influenced the measurement outcome. However, when appropriate analysis was used, the primary care system was able to quantify the degree of change and can be recommended depending on the accuracy needed to diagnose a condition. Lower-resolution scanners may underestimate complex changes when measuring at the micron level.

Reliability and validity of a new classification of MIH based on severity.

OBJECTIVES: To describe a new molar-incisor hypomineralization (MIH) severity scoring system (MIH-SSS) that focuses on the defects' severity and to assess the system's validity and reliability over 3 years. MATERIALS AND METHODS: One hundred eighty-one children diagnosed with MIH were examined by MIH-SSS. For reliability assessment, 15-20 children were examined twice, and analyses were performed at the tooth level at four different cutoff points. Follow-up examinations were performed over 36 months. Only teeth presenting MIH opacities at baseline were assessed. Odds ratios were calculated to evaluate the chance of post-eruptive breakdown (PEB) occurrence related to the colors of MIH defects. Survival curves were created for different types of teeth (molars and incisors) based on white and yellow opacities. The Kaplan-Meier method was used with PEB as the outcome. RESULTS: According to the MIH-SSS, kappa values ranged from 0.82 to 0.88. Regarding the longitudinal evaluation, for molars and incisors, yellow/brown opacities had a significantly higher chance to evolve to dentin breakdown compared with white/creamy opacities (OR = 2.54, OR = 10.58, respectively). Survival analysis showed that the occurrence of PEB was more frequent in the first evaluation period (12 months). CONCLUSION: MIH-SSS, which provides detailed information about MIH severity, is a valid instrument presenting high reliability. Yellow/brown opacities progressed more than did white/creamy opacities. CLINICAL RELEVANCE: It is of paramount importance to detect any surface breakdown as early as possible to be able to avoid pain and caries progression. Moreover, this is the first paper that shows survival curves for MIH enamel breakdown over time.

Evaluation of hyoid movement during swallowing using a bend sensor.

BACKGROUND: Movement of the hyoid and laryngeal complex is critical for preventing aspiration, as well as smooth bolus passage through the pharynx. We have developed a non-invasive system for measuring laryngeal movement during swallowing with a bend sensor and have already reported the time coordination between the signal waveform from the sensor and hyoid movement. OBJECTIVE: The aim of this study was to clarify the quantitative association between the output value of the sensor and hyoid movement during swallowing. METHODS: A small bend sensor was fixed on the skin surface along the midline of the neck of 13 healthy men (mean age, 30.8 ± 4.5 years). Laryngeal and hyoid movements during swallowing of 5 mL of water were recorded synchronously by the bend sensor and videofluorography. The relationship between the bend sensor output value (LM value) and hyoid position (x- and y-axis displacements) by videofluorography from the onset to the offset of the signal waveform was analysed for all tasks and for each task using Pearson's correlation coefficients. RESULTS: There was a positive correlation between the LM value and hyoid position for all tasks (x-axis displacement: r = .647, y-axis displacement: r = .233). In particular, there was a moderate to high correlation between the LM value and x-axis displacement for each task (.453 ≤ r ≤ .934). CONCLUSION: The LM value can be a quantitative parameter of anterior hyoid movement during swallowing that might be associated with bolus flow and upper oesophageal sphincter opening.

Surgical wound infection following open humeral fracture caused by Mycobacterium houstonense: a case report.

BACKGROUND: Historically Mycobacterium houstonense belongs to the unnamed third biovariant complex of the Mycobacterium fortuitum group, which are sorbitol positive. To date, there have been few reports of human infection induced by M. houstonense worldwide. CASE PRESENTATION: We describe the case of a 68-year-old man with surgical wound infection, following an open humeral fracture, caused by M. houstonense and Escherichia coli. An implant bone plate had been embedded for internal fixation during surgery on the humeral fracture previously. A week later E. coli was isolated from the skin wound secretions. Cefoperazone-sulbactam was used for treatment for two weeks but the infection was not controlled, with a subsequent risk of deep wound infection. External fixation of the fracture was then performed instead of internal fixation. Ten days later, M. houstonense was isolated from new wound secretions. M. houstonense was identified by the molecular sequencing method. The TREK Diagnostic System was used to test the susceptibility to antibiotics by the microbroth dilution method. Levofloxacin and amikacin were used for treatment according to the results of the susceptibility test and the patient's condition obviously improved. CONCLUSION: To the best of our knowledge, this is the first case in China of human surgical wound infection caused by M. houstonense following open humeral fracture. The combination of levofloxacin and amikacin was effective in the treatment of M. houstonense infection.

Multiphoton Microscopy for Caries Detection with ICDAS Classification.

Dentin carious lesion is a dynamic process that involves demineralization and collagen denaturation. Collagen type I is the major protein in dentin and it has been investigated based on its optical properties. Multiphoton microscopy (MPM) is a nonlinear imaging technique that reveals the caries process using the collagen two-photon excitation fluorescence (2PEF) and its second-harmonic generation (SHG). Combining the histological and the International Caries Detection and Assessment System (ICDAS) classifications with nonlinear optical spectroscopy (NLOS), 2PEF and SHG intensities of enamel and dentin were highly altered during the caries process. It has been proven that the ratio SHG/2PEF is a relevant indicator of the organic matrix denaturation [Terrer et al.: J Dent Res 2016; 96: 574-579]. In the present study, a series of measurable signals is made to detect early stages of carious lesion according to the ICDAS classification and to explore the relationship between these measures and the ICDAS scale. Comparison of the efficiency of nonlinear optical signals for caries detection with the ICDAS classification is essential to evaluate their potential for clinical application. In our study, the use of the NLOS measured by MPM allowed us to monitor a quantitative parameter (SHG/2PEF ratio) according to the dentin carious lesion state (ICDAS and histological examination). Three coherent new groups were defined (ICDAS 0/1; ICDAS 2/3; ICDAS 4/5/6), where the carious process can be clearly described with a statistically significant decrease of the SHG/2PEF ratio.

Mini dental assessment: a simple screening test for non-dental staff.

OBJECTIVE: The objective of this study was to develop a simple tool for the assessment of possible dental treatment needs (DTN) for non-dental professionals (Mini Dental Assessment, MDA). To keep the assessment universal, we aimed to base it on the patient's history and a simple chewing efficiency test (CET) as the dental status is a known determinant for chewing efficiency. MATERIALS & METHODS: The assessment was developed using data from 169 patients from two sites (University Hospital Giessen, St. Bonifatius Hospital Lingen, both Germany). In all patients, a dental examination was performed, the denture status was evaluated (based on the California Dental Association criteria; CDA criteria), and the DTN was determined. In addition, the time since the patient's last visit to a dentist (TLVD) and denture age (DA) were assessed. Furthermore, a CET was carried out and the comminution score was determined (CETS). RESULTS: In total, 108 patients required dental treatment. The mean value (±SD) was 2.9 ± 0.9 score points for the DTN, 2.5 ± 3.8 years for the TLVD, and 10.8 ± 8.9 years for the DA. There was a significant correlation (Spearman, P < .05) between the DTN and degree of comminution (3.4 ± 1.8). Based on the results of the statistical analysis, the intended assessment tool was developed using the variables CETS, TLVD, and DA weighed by their respective regression coefficients (10:3:1). Subsequently, the resulting MDA score (51.32 ± 28.14) was calculated. A sensitivity/specificity analysis was conducted and a receiver operating characteristic curve was calculated (SPSS 17.0, area under curve 0.805; 95 % CI 0.738-0.873). CONCLUSION: It can be concluded that the dental status of elderly patients is reflected in the outcome of the MDA. However, ongoing validation is needed. TRIAL REGISTRATION: DRKS00003219.

Editorial: Distinguishing between the challenges posed by surface and deep forms of heterogeneity to diagnostic systems: do we need a new approach to subtyping of child and adolescent psychiatric disorders.

Diagnostic formulations attempt to impose order on the messy reality of psychopathological phenomena. By doing this, so their advocates argue, they provide both the platform necessary for systematic scientific study, and, crucially, the bridge of shared terms and concepts vital if psychiatric science is to be truly translational; where scientific endeavour is guided by clinical priorities and, in-turn, scientific findings innovate clinical practice. The diagnostic schemes we currently work with, taking DSM-5 as the obvious case, are the product of an interesting historical process of ongoing revision - at the same time pragmatic and scientific. On the one hand, it is a process both anchored firmly in historical precedent and constrained by the practical needs of clinicians, patients and health insurance companies. On the other hand, it is a process open to new empirical data about how to best cluster symptomatic expressions and differentiate clinical presentations - so that over historical time diagnostic categories achieve an increasingly accurate mapping of the taxonomy (i.e., underlying structure), and related pathophysiology, of psychiatric phenomenon. Resolving the inevitable tensions that arise when trying to reconcile these pragmatic (economic and professional) and scientific priorities has proved to be both challenging and contentious. The study of heterogeneity as exemplified by the articles highlighted in this editorial indicate a range of different approaches that can be effectively used to refine psychiatric taxonomies by incorporating developmental and pathophysiological data to help identify new putative subtypes of potential therapeutic significance.

Natural Language Processing: Chances and Challenges in Dentistry.

INTRODUCTION: Natural language processing (NLP) is an intersection between Computer Science and Linguistic which aims to enable machines to process and understand human language. We here summarized applications and limitations of NLP in dentistry. DATA AND SOURCES: Narrative review. FINDINGS: NLP has evolved increasingly fast. For the dental domain, relevant NLP applications are text classification (e.g., symptom classification) and natural language generation and understanding (e.g., clinical chatbots assisting professionals in office work and patient communication). Analyzing large quantities of text will allow understanding diseases and their trajectories and support a more precise and personalized care. Speech recognition systems may serve as virtual assistants and facilitate automated documentation. However, to date, NLP has rarely been applied in dentistry. Existing research focuses mainly on rule-based solutions for narrow tasks. Technologies such as Recurrent Neural Networks and Transformers have been shown to surpass the language processing capabilities of such rule-based solutions in many fields, but are data-hungry (i.e., rely on large amounts of training data), which limits their application in the dental domain at present. Technologies such as federated or transfer learning or data sharing concepts may allow to overcome this limitation, while challenges in terms of explainability, reproducibility, generalizability and evaluation of NLP in dentistry remain to be resolved for enabling approval of such technologies in medical devices and services. CONCLUSIONS: NLP will become a cornerstone of a number of applications in dentistry. The community is called to action to improve the current limitations and foster reliable, high-quality dental NLP. CLINICAL SIGNIFICANCE: NLP for text classification (e.g., dental symptom classification) and language generation and understanding (e.g., clinical chatbots, speech recognition) will support administrative tasks in dentistry, provide deeper insights for clinicians and support research and education.