ChatGPT’s performance in German OB/GYN exams – paving the way for AI-enhanced medical education and clinical practice

BackgroundChat Generative Pre-Trained Transformer (ChatGPT) is an artificial learning and large language model tool developed by OpenAI in 2022. It utilizes deep learning algorithms to process natural language and generate responses, which renders it suitable for conversational interfaces. ChatGPT’s potential to transform medical education and clinical practice is currently being explored, but its capabilities and limitations in this domain remain incompletely investigated. The present study aimed to assess ChatGPT’s performance in medical knowledge competency for problem assessment in obstetrics and gynecology (OB/GYN).MethodsTwo datasets were established for analysis: questions (1) from OB/GYN course exams at a German university hospital and (2) from the German medical state licensing exams. In order to assess ChatGPT’s performance, questions were entered into the chat interface, and responses were documented. A quantitative analysis compared ChatGPT’s accuracy with that of medical students for different levels of difficulty and types of questions. Additionally, a qualitative analysis assessed the quality of ChatGPT’s responses regarding ease of understanding, conciseness, accuracy, completeness, and relevance. Non-obvious insights generated by ChatGPT were evaluated, and a density index of insights was established in order to quantify the tool’s ability to provide students with relevant and concise medical knowledge.ResultsChatGPT demonstrated consistent and comparable performance across both datasets. It provided correct responses at a rate comparable with that of medical students, thereby indicating its ability to handle a diverse spectrum of questions ranging from general knowledge to complex clinical case presentations. The tool’s accuracy was partly affected by question difficulty in the medical state exam dataset. Our qualitative assessment revealed that ChatGPT provided mostly accurate, complete, and relevant answers. ChatGPT additionally provided many non-obvious insights, especially in correctly answered questions, which indicates its potential for enhancing autonomous medical learning.ConclusionChatGPT has promise as a supplementary tool in medical education and clinical practice. Its ability to provide accurate and insightful responses showcases its adaptability to complex clinical scenarios. As AI technologies continue to evolve, ChatGPT and similar tools may contribute to more efficient and personalized learning experiences and assistance for health care providers

Highly Biaxially Strained Silicene on Au(111)

Many of graphene’s remarkable properties arise from its linear dispersion of the electronic states, forming a Dirac cone at the K points of the Brillouin zone. Silicene, the 2D allotrope of silicon, is also predicted to show a similar electronic band structure, with the addition of a tunable bandgap, induced by spin–orbit coupling. Because of these outstanding electronic properties, silicene is considered as a promising building block for next-generation electronic devices. Recently, it has been shown that silicene grown on Au(111) still possesses a Dirac cone, despite the interaction with the substrate. Here, to fully characterize the structure of this 2D material, we investigate the vibrational spectrum of a monolayer silicene grown on Au(111) by polarized Raman spectroscopy. To enable a detailed ex situ investigation, we passivated the silicene on Au(111) by encapsulating it under few layers hBN or graphene flakes. The observed spectrum is characterized by vibrational modes that are strongly red-shifted with respect to the ones expected for freestanding silicene. By comparing low-energy electron diffraction (LEED) patterns and Raman results with first-principles calculations, we show that the vibrational modes indicate a highly (>7%) biaxially strained silicene phase.This work was funded by the Fonds zur Förderung der Wissenschaftlichen Forschung (FWF), Austria (Project P29244-N27). We also acknowledge financial support by the Ministerio de Economía, Industria y Competitividad (MINECO) under Grant FEDER-MAT2017-90024-P and the Severo Ochoa Centres of Excellence Program under Grant CEX2019-000917-S, and by the Generalitat de Catalunya under Grant 2017 SGR 1506. The project i-LINK action LINKA20047 funded by CSIC is also acknowledged for financial support. R.R. acknowledges useful discussions with Mariusz Krawiec. CzechNanoLab Project LM2018110 funded by MEYS CR is gratefully acknowledged for the financial support of the measurements at CEITEC Nano Research Infrastructure. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT, Japan, Grant JPMXP0112101001, JSPS KAKENHI Grant JP20H00354, and the CREST(JPMJCR15F3), JST.Peer reviewe

Appearance-based rejection sensitivity in body dysmorphic disorder and eating disorders : Potential of the feature for disorder differentiation

HintergrundDie körperdysmorphe Störung (KDS) und die Essstörungen (ESS) weisen erhebliche Symptomüberschneidungen auf, was die Differenzialdiagnose erschwert. Die Psychopathologie der beiden Störungen deutet auf die aussehensbezogene Zurückweisungssensitivität („appearance-based rejection sensitivity“, ARS) als mögliches differenzierendes Merkmal hin.Ziel der ArbeitDie Studie soll Hinweise zu einer Verbesserung der Differenzialdiagnostik zwischen KDS und ESS geben. Dazu wurden die Störungen hinsichtlich der ARS miteinander verglichen. Auf Basis der bisherigen empirischen Forschung wurde davon ausgegangen, dass bei KDS höhere ARS-Werte vorliegen als bei ESS. Weiterhin sollte eine höhere Varianzaufklärung von KDS an der ARS unter Konstanthaltung von Störvariablen (sozialängstliche Symptome, Body-Mass-Index, Geschlecht) geprüft werden.Material und MethodenEine Verfügbarkeitsstichprobe (n = 736) füllte online die Appearance-based Rejection Sensitivity Scale, die Liebowitz Social Anxiety Scale, den Eating Disorder Examination Questionnaire und ein DSM-5-Screening zu KDS aus.ErgebnisseTeilnehmer mit komorbid positivem KDS-ESS-Screening erzielten den höchsten ARS-Gesamtwert aber ähnlich hohe Werte wie Teilnehmer mit positivem ESS-Screening. Beide Gruppen erzielten signifikant höhere Werte als Teilnehmer mit positivem KDS-Screening, welche wiederum signifikant höhere Werte erzielten als symptomfreie Teilnehmer. Die Regressionsanalyse bestätigte eine höhere Varianzaufklärung an der ARS durch ESS als durch KDS bei Konstanthaltung von Störvariablen.DiskussionDie ARS konnte nicht als differenzierendes Merkmal zwischen KDS und ESS im Sinne der Hypothesen bestätigt werden. Allerdings könnten hohe ARS-Werte einen Hinweis auf eine ESS oder KDS darstellen, sehr hohe Werte für komorbide ESS-KDS-Symptome. Dies sollte diagnostisch abgesichert und ggf. in der Therapie berücksichtigt werden.publishe

Silicene Passivation by Few-Layer Graphene

The final publication is available via https://doi.org/10.1021/acsami.8b20751.The stabilization of silicene at ambient conditions is essential for its characterization, future processing, and device integration. Here, we demonstrate insitu encapsulation of silicene on Ag(111) by exfoliated few-layer graphene (FLG)flakes, allowing subsequent Raman analysis under ambient conditions. Raman spectroscopy measurements proved that FLG capping serves as an effective passivation, preventing degradation of silicene for up to 48 h.The acquired data are consistent with former in situ Raman measurements, showing two characteristic peaks, located at 216 and 515 cm−1. Polarization-dependent measurements allowed to identify the two modes as A and E, demonstrating that the symmetry properties of silicene are unaltered by the capping process.Austrian Science Funds (FWF

Neural Correlates of Own- and Other-Face Perception in Body Dysmorphic Disorder

Background: Body dysmorphic disorder (BDD) is characterized by an excessive preoccupation with one or more perceived flaws in one’s own appearance. Previous studies provided evidence for deficits in configural and holistic processing in BDD. Preliminary evidence suggests abnormalities at an early stage of visual processing. The present study is the first examining early neurocognitive perception of the own face in BDD by using electroencephalography (EEG). We investigated the face inversion effect, in which inverted (upside-down) faces are disproportionately poorly processed compared to upright faces. This effect reflects a disruption of configural and holistic processing, and in consequence a preponderance of featural face processing. Methods: We recorded face-sensitive event-related potentials (ERPs) in 16 BDD patients and 16 healthy controls, all unmedicated. Participants viewed upright and inverted (upside-down) images of their own face and an unfamiliar other face, each in two facial emotional expressions (neutral vs. smiling). We calculated the early ERP components P100, N170, P200, N250, and the late positive component (LPC), and compared amplitudes among both groups. Results: In the early P100, no face inversion effects were found in both groups. In the N170, both groups exhibited the common face inversion effects, with significantly larger N170 amplitudes for inverted than upright faces. In the P200, both groups exhibited larger inversion effects to other (relative to own) faces, with larger P200 amplitudes for other upright than inverted faces. In the N250, no significant group differences were found in face processing. In the LPC, both groups exhibited larger inversion effects to other (relative to own) faces, with larger LPC amplitudes for other inverted than upright faces. These overall patterns appeared to be comparable for both groups. Smaller inversion effects to own (relative to other) faces were observed in none of these components in BDD, relative to controls. Conclusions: The findings suggest no evidence for abnormalities at all levels of early face processing in our observed sample of BDD patients. Further research should investigate the neural substrates underlying BDD symptomatology

Neural correlates of emotional interference in social anxiety disorder

Disorder-relevant but task-unrelated stimuli impair cognitive performance in social anxiety disorder (SAD); however, time course and neural correlates of emotional interference are unknown. The present study investigated time course and neural basis of emotional interference in SAD using event-related functional magnetic resonance imaging (fMRI). Patients with SAD and healthy controls performed an emotional stroop task which allowed examining interference effects on the current and the succeeding trial. Reaction time data showed an emotional interference effect in the current trial, but not the succeeding trial, specifically in SAD. FMRI data showed greater activation in the left amygdala, bilateral insula, medial prefrontal cortex (mPFC), dorsal anterior cingulate cortex (ACC), and left opercular part of the inferior frontal gyrus during emotional interference of the current trial in SAD patients. Furthermore, we found a positive correlation between patients’ interference scores and activation in the mPFC, dorsal ACC and left angular/supramarginal gyrus. Taken together, results indicate a network of brain regions comprising amygdala, insula, mPFC, ACC, and areas strongly involved in language processing during the processing of task-unrelated threat in SAD. However, specifically the activation in mPFC, dorsal ACC, and left angular/supramarginal gyrus is associated with the strength of the interference effect, suggesting a cognitive network model of attentional bias in SAD. This probably comprises exceeded allocation of attentional resources to disorder-related information of the presented stimuli and increased self-referential and semantic processing of threat words in SAD

Psychometric evaluation of the German version of the Yale-Brown Obsessive-Compulsive Scale Modified for Body Dysmorphic Disorder (BDD-YBOCS)

The Yale-Brown Obsessive-Compulsive Scale Modified for Body Dysmorphic Disorder (BDD-YBOCS) is a clinician-administered interview to assess symptom severity in individuals with a BDD diagnosis. It has been translated into German and disseminated into research and practice. However, the psychometric properties of the German version have not been thoroughly evaluated. Therefore, we investigated its psychometric properties, factor structure and provided normative data. Our study included a large pooled sample comprising 350 outpatients with a BDD diagnosis (mean age = 30.35 years, SD = 10.15; gender: 70.6% female, 28.9% male, 0.6% unspecified). Psychometric data supported a good internal consistency of the BDD-YBOCS total score (α = 0.81, ω = 0.86) and an excellent interrater-reliability (ICC = 0.96). The BDD-YBOCS correlated moderately with other measures of BDD symptom severity. Confirmatory factor analysis favored a two-factor structure representing obsessions versus compulsions over a one-factor structure, with the quality of the proposed two-factor structure still being poor. Normative data indicated that BDD-YBOCS scores between 21 and 34 can be considered as typical range in an outpatient sample with a wide range of BDD symptom severity. In conclusion, the German BDD-YBOCS is a brief and psychometrically supported clinician-rated instrument for the measurement of BDD severity.publishe

An empirically derived recommendation for the classification of body dysmorphic disorder: Findings from structural equation modeling

Body dysmorphic disorder (BDD), together with its subtype muscle dysmorphia (MD), has been relocated from the Somatoform Disorders category in the DSM-IV to the newly created Obsessive-Compulsive and Related Disorders category in the DSM-5. Both categorizations have been criticized, and an empirically derived classification of BDD is lacking. A community sample of N = 736 participants completed an online survey assessing different psychopathologies. Using a structural equation modeling approach, six theoretically derived models, which differed in their allocation of BDD symptoms to various factors (i.e. general psychopathology, somatoform, obsessive-compulsive and related disorders, affective, body image, and BDD model) were tested in the full sample and in a restricted sample (n = 465) which indicated primary concerns other than shape and weight. Furthermore, measurement invariance across gender was examined. Of the six models, only the body image model showed a good fit (CFI = 0.972, RMSEA = 0.049, SRMR = 0.027, TLI = 0.959), and yielded better AIC and BIC indices than the competing models. Analyses in the restricted sample replicated these findings. Analyses of measurement invariance of the body image model showed partial metric invariance across gender. The findings suggest that a body image model provides the best fit for the classification of BDD and MD. This is in line with previous studies showing strong similarities between eating disorders and BDD, including MD. Measurement invariance across gender indicates a comparable presentation and comorbid structure of BDD in males and females, which also corresponds to the equal prevalence rates of BDD across gender