Expert Observers Research Articles

Why Did the Earwitnesses to the John F. Kennedy Assassination Not Agree About the Location of the Gunman?

Earwitnesses to the 1963 assassination of President John F. Kennedy (JFK) did not agree about the location of the gunman even though their judgments about the number and timing of the gunshots were reasonably consistent. Even earwitnesses at the same general location disagreed. An examination of the acoustics of supersonic bullets and the characteristics of human sound localization help explain the general disagreement about the origin of the gunshots. The key fact is that a shock wave produced by the supersonic bullet arrived prior to the muzzle blast for many earwitnesses, and the shock wave provides erroneous information about the origin of the gunshot. During the government's official re-enactment of the JFK assassination in 1978, expert observers were highly accurate in localizing the origin of gunshots taken from either of two locations, but their supplementary observations help explain the absence of a consensus among the earwitnesses to the assassination itself.

Review of automated performance metrics to assess surgical technical skills in robot-assisted laparoscopy

Robot-assisted laparoscopy is a safe surgical approach with several studies suggesting correlations between complication rates and the surgeon's technical skills. Surgical skills are usually assessed by questionnaires completed by an expert observer. With the advent of surgical robots, automated surgical performance metrics (APMs)-objective measures related to instrument movements-can be computed. The aim of this systematic review was thus to assess APMs use in robot-assisted laparoscopic procedures. The primary outcome was the assessment of surgical skills by APMs and the secondary outcomes were the association between APM and surgeon parameters and the prediction of clinical outcomes. A systematic review following the PRISMA guidelines was conducted. PubMed and Scopus electronic databases were screened with the query "robot-assisted surgery OR robotic surgery AND performance metrics" between January 2010 and January 2021. The quality of the studies was assessed by the medical education research study quality instrument. The study settings, metrics, and applications were analysed. The initial search yielded 341 citations of which 16 studies were finally included. The study settings were either simulated virtual reality (VR) (4 studies) or real clinical environment (12 studies). Data to compute APMs were kinematics (motion tracking), and system and specific events data (actions from the robot console). APMs were used to differentiate expertise levels, and thus validate VR modules, predict outcomes, and integrate datasets for automatic recognition models. APMs were correlated with clinical outcomes for some studies. APMs constitute an objective approach for assessing technical skills. Evidence of associations between APMs and clinical outcomes remain to be confirmed by further studies, particularly, for non-urological procedures. Concurrent validation is also required.

A Suggested Model for Organizing the Relationships among Agricultural Extension, Research and Educational Institutions in The Sulaymani Governorate

This research aimed at a proposal to regulate the relationships among extension, research and educational agricultural institutions in Sulaymani Governorate, by diagnosing the personal variables of the respondents, and identifying the reality of organizing relationships between these institutions, leading to preparing a proposed model for organizing relations between them. The research population included the agricultural organizations represented by (Agricultural Extension Directorate, Agricultural Research Directorate, Agricultural Colleges and Institutes), and a proportional stratified random Sample of 15% was chosen from all organizations, the total of the instructor sample is 85 respondents. The proposed model was prepared according to the following procedures: literature and forms, expert observations, review of research and articles, conducting field visits, documents and records. 3 fields, 12 elements and 168 paragraphs were developed, all of which formed the initial formula of the model. The model was presented in its initial form to a group of experts in the field of agricultural extension and management, and after taking their observations into account; the model now includes 3 fields, 12 elements and 148 paragraphs. The research found that there is no process of organizing the relationships between the studied institutions, and showed that all respondents agreed on the paragraphs of the proposed model. And recommends its application in real agricultural work in Sulaymani province.

Real-Time 3D Tracking of Laparoscopy Training Instruments for Assessment and Feedback.

Assessment of minimally invasive surgical skills is a non-trivial task, usually requiring the presence and time of expert observers, including subjectivity and requiring special and expensive equipment and software. Although there are virtual simulators that provide self-assessment features, they are limited as the trainee loses the immediate feedback from realistic physical interaction. The physical training boxes, on the other hand, preserve the immediate physical feedback, but lack the automated self-assessment facilities. This study develops an algorithm for real-time tracking of laparoscopy instruments in the video cues of a standard physical laparoscopy training box with a single fisheye camera. The developed visual tracking algorithm recovers the 3D positions of the laparoscopic instrument tips, to which simple colored tapes (markers) are attached. With such system, the extracted instrument trajectories can be digitally processed, and automated self-assessment feedback can be provided. In this way, both the physical interaction feedback would be preserved and the need for the observance of an expert would be overcome. Real-time instrument tracking with a suitable assessment criterion would constitute a significant step towards provision of real-time (immediate) feedback to correct trainee actions and show them how the action should be performed. This study is a step towards achieving this with a low cost, automated, and widely applicable laparoscopy training and assessment system using a standard physical training box equipped with a fisheye camera.

A novel technique for automating stiffness measurement and emphasizing the main wave: Coherent-wave auto-selection (CHASE)

This study aims to develop and assess a new automated processing technique in MR elastography (MRE), namely coherent-wave auto-selection (CHASE). CHASE enables automatic selection of the region of interest (ROI) for stiffness measurement by extraction of the coherent wave region (CHASE ROI), and it improves the reconstruction of stiffness by a directional filter oriented along the main wave in each pixel (CHASE filtering). In this study, MRE of a phantom and of the liver of four healthy volunteers was performed. To investigate the potential of CHASE, this study assessed the CHASE according to three indices through the phantom study: 1) agreement on the ROI settings between CHASE and expert observers, 2) noise dependency, and 3) effect of the CHASE on stiffness variability within the CHASE ROI. The agreements on the ROI settings were analyzed by Cohen's kappa coefficient (κ). The noise dependency was analyzed by the mean absolute percentage errors (MAPEs) within the ROI between low (20%–80% amplitudes) and high vibration amplitudes (100% amplitude). The stiffness variability was assessed by standard deviation (SD) within the ROI. In the volunteer study, agreements on the ROI settings (or stiffness value) and stiffness variability within the CHASE ROI were assessed using κ-value (or intraclass correlation coefficient: ICC) and coefficient of variation, respectively. The results showed close agreement on the ROI settings and stiffness (κ-value: greater than 0.61 in both the phantom and volunteer studies, ICC: 0.97 in the volunteer study). The MAPEs within the CHASE ROI were much smaller than those in the whole region of the phantom (CHASE ROI vs. the whole region at 20% amplitude: 10.3% vs. 50.8%). Moreover, in both the phantom and volunteer studies, the stiffness variation within the CHASE ROI was smaller in the elastogram processed with CHASE filtering than in the unprocessed one. Our results demonstrated that the CHASE has high robustness against noise and the potential to provide ROI settings for stiffness measurement comparable to expert observers, as well as improve the reconstruction of stiffness.

Methodology of Functional and Technical Evaluation of Cooperative Intelligent Transport Systems and Its Practical Application

In the area of smart cities, great emphasis is placed on many different fields such as energetics, information systems, and transportation. All of these should lead to a simplification of life thanks to smart technologies. If we talk about the transportation field, the main issues related to this area are safety, traffic efficiency, or the environment. Another condition is the successful acceptance of any new technology by its users. Cooperative systems prove to be a suitable solution for these issues, especially in urban areas. Today, pilot implementations of cooperative systems in European countries are being carried out. However, before they are put into full operation, they need to be tested, evaluated, and assessed. This article focuses on the latter two points, i.e., evaluation and assessment of the cooperative systems. For this purpose, a methodology was created, which describes the procedure chosen in the evaluation and assessment of cooperative systems in the Czech Republic and a demonstration of its use by example. The methodology is focused on three main areas, which in this case are functional evaluation, user acceptance, and impact assessment. For the area of user acceptance, the main source was questionnaires, impact assessment relied on measured data while functional evaluation was based on discussions with the drivers, evaluating the cooperative systems, the measured data, and the expert observations. All collected and measured data were then processed and some of the results of the evaluation of the selected service are presented at the end of this article.

A national study on the inter-observer variability in the delineation of organs at risk in the brain

Background The Danish Neuro Oncology Group (DNOG) has established national consensus guidelines for the delineation of organs at risk (OAR) structures based on published literature. This study was conducted to finalise these guidelines and evaluate the inter-observer variability of the delineated OAR structures by expert observers. Material and methods The DNOG delineation guidelines were formed by participants from all Danish centres that treat brain tumours with radiotherapy. In a two-day workshop, guidelines were discussed and finalised based on a pilot study. Following this, the ten participants contoured the following OARs on T1-weighted gadolinium enhanced MRI from 13 patients with brain tumours: optic tracts, optic nerves, chiasm, spinal cord, brainstem, pituitary gland and hippocampus. The metrics used for comparison were the Dice similarity coefficient (Dice), mean surface distance (MSD) and others. Results A total of 968 contours were delineated across the 13 patients. On average eight (range six to nine) individual contour sets were made per patient. Good agreement was found across all structures with a median MSD below 1 mm for most structures, with the chiasm performing the best with a median MSD of 0.45 mm. The Dice was as expected highly volume dependent, the brainstem (the largest structure) had the highest Dice value with a median of 0.89 whereas smaller volumes such as the chiasm had a Dice of 0.71. Conclusion Except for the caudal definition of the spinal cord, the variances observed in the contours of OARs in the brain were generally low and consistent. Surface mapping revealed sub-regions of higher variance for some organs. The data set is being prepared as a validation data set for auto-segmentation algorithms for use within the Danish Comprehensive Cancer Centre – Radiotherapy and potential collaborators.

A convolutional neural network architecture designed for the automated survey of seabird colonies

AbstractSatellite imagery is now well established as a method of finding and estimating the abundance of Antarctic penguin colonies. However, the delineation and classification of penguin colonies in sub‐meter satellite imagery has required the use of expert observers and is highly labor intensive, precluding regular censuses at the pan‐Antarctic scale. Here we present the first automated pipeline for the segmentation and classification of seabird colonies in high‐resolution satellite imagery. Our method leverages site‐fidelity by using images from previous years to improve classification performance but is robust to georegistration artifacts imposed by misalignment between sensors or terrain correction. We use a segmentation network with an additional branch that extracts the useful information from the prior mask of the input image. This prior branch provides the main model information on the location and size of guano in a prior annotation yet automatically learns to compensate for potential misalignment between the prior mask and the input image being classified. Our approach outperforms the previous approach by 44%, improving the average Intersection‐over‐Union segmentation score from 0.34 to 0.50. While penguin guano remains a challenging target for segmentation due to its indistinct and highly variable appearance, the inclusion of prior information represents a key step toward automated image annotation for population monitoring. Moreover, this method can be adapted for other ecological applications where the dynamics of landscape change are slow relative to the repeat frequency of available imagery and prior information may be available to aid with image annotation.

Countering Bias in Assessment.

Assessments can provide meaningful performance data from expert observers, but this information is prone to harmful bias. Such assessment bias disproportionately affects trainees who do not resemble or share identities with those doing the assessment.1 While hundreds of cognitive biases exist, some have particularly pernicious influences when building and sustaining diversity in medicine, with subtle differences in individual performance ratings systematically perpetuating the exclusion of marginalized groups.1Bias affects our perceptions of another's knowledge, ability, professionalism, and readiness for independent practice.2 Over repeated assessments, these biases can result in an amplification cascade,1 a phenomenon in which small differences in assessed performance lead to larger differences in grades and selection for awards, favoring well-represented individuals and hindering underrepresented in medicine (UiM) trainees in achieving training success.3 Eliminating harmful effects of cognitive biases requires a multilevel response. Recognizing that bias and cognitive error cannot be “trained out” of individuals,4 systems can be put in place to create more equitable assessment. We must start by critically evaluating the tools, processes, and outcomes of our existing assessments.3 Equitable assessments are criterion-based, encompass multiple dimensions of optimal patient care, and take place in the context of a longitudinal relationship.5 Assessment should be reoriented from a deficit-focused lens toward a growth-focused model that uses goal setting, differentiated assessments, direct observation, and frequent feedback, both positive and critical.5

Lesion detection in 18F-sodium fluoride bone imaging: a comparison of attenuation-corrected versus nonattenuation-corrected PET reconstructions from modern PET-CT systems.

An earlier study demonstrated comparable lesion detection between attenuation-corrected (AC) and nonattenuation-corrected (NAC) 18F-sodium fluoride (NaF) PET images, which is relevant for computed tomography (CT) radiation dose-saving. However, this finding may not be applicable to newer systems. The aim was to compare lesion detection between AC and NAC NaF PET images on modern PET-CT systems. One expert and one nonexpert observer retrospectively surveyed NaF PET data in 25 breast cancer patients. At both lesion and patient level, each observer classified bone abnormalities as malignant, equivocal or benign, from NAC and AC PET images in the absence of CT. Expert interpretation of NaF PET-CT with the review of all diagnostic imaging/pathology reports for at least the subsequent 12 months provided reference standard metastases status at the patient level. Two-tailed Wilcoxon signed-rank tests measured statistically significant differences in total lesion detection between AC and NAC PET. Quadratic-weighted kappa score measured agreement in patient metastases status between observers. On a lesion-basis, AC PET images showed significantly more lesions than NAC for both the expert (122 versus 96; P = 0.002) and nonexpert (146 versus 132; P = 0.036) observers, with a large number of patients demonstrating disparity between AC and NAC images. For metastases status at the patient level without CT, NAC PET showed slightly better diagnostic accuracy than AC due to fewer false-positive results, as fewer lesions were identified. AC PET data provided superior lesion detection to NAC in NaF bone examinations and are thus required for clinical interpretation.

DEVELOPING COMIC MEDIA ABOUT HUMAN INTERACTION WITH THE ENVIRONMENT TO IMPROVE CRITICAL THINKING SKILLS

Students' critical thinking has not been maximally trained in learning since learning activities are only memorizing to meet the demands of passing the assessment. Students are less able to understand, build, and criticize arguments about a problem, especially in social studies learning. This study aimed to determine the feasibility of comic media material about human interaction with the environment to improve the critical thinking skills of fifth grade students. This type of research was research and development (Research and Development) with a 4D model. This research was conducted online using Zoom platform, Google forms, and Ms. Teams that was carried out synchronously and asynchronously due to the Covid-19 pandemic. Data were collected through the expert validation stage and observation sheets, student response questionnaires and critical thinking tests (pretest and posttest) for the teacher and student activity. Furthermore, the data were analyzed by quantitative and descriptive techniques. The results showed that: (1) comic media was in the very feasible category with a percentage of 82%, (2) it was practical based on teacher activity observations with a percentage of 94% with very active category, 95% for student activity with very active category and student response questionnaires was 93% with very good category, (3) it was effective based on the result of N-gain on the critical thinking test, which was 0.53 (medium category). Thus, comic media in social studies learning was declared valid, practical and effective in improving students’ critical thinking skills at fifth grade of elementary school.

Characterization and Pilot Human Trial of Dedicated Breast Ring Positron Emission Tomography (BRPET) System

We describe the design and performance of BRPET, a novel dedicated breast PET (dbPET) scanner designed to maximize visualization of posterior regions of the breast. BRPET uses prone imaging geometry and a 12-module detector ring built from pixelated LYSO crystals coupled to position sensitive photomultiplier tubes (PSPMTs). Optical coupling via slanted plastic fiber optic light guides permits partial insertion of the crystals into the exam table’s breast aperture. Image quality testing procedures were adapted from the NEMA NU4-2008 protocol. Two additional phantom tests quantified the posterior extent of the usable volume of view (VoV). BRPET axial, radial, and tangential FWHM spatial resolutions at the isocenter were 1.8, 1.7, and 1.9 mm, respectively. The peak absolute system sensitivity was 0.97% using an energy window of 460–562 keV. The peak noise equivalent counting rate was 5.33 kcps at 21.6 MBq. The scanner VoV extends to within ~6 mm of the plane defining the location of the chest wall. A pilot human study (n = 10) compared the diagnostic performance of FDG-BRPET to that of contrast enhanced MRI (CEMRI), with biopsy as ground truth. Averaged over three expert human observers, the sensitivity/specificity for BRPET was 0.93/1.0, compared to 1.0/0.25 for CEMRI.

Ultrafast Computation of Left Ventricular Ejection Fraction by Using Temporal Intensity Variation in Cine Cardiac Magnetic Resonance.

Cardiac magnetic resonance enables comprehensive cardiac evaluation; however, intense time and labor requirements for data acquisition and processing have discouraged many clinicians from using it. We have developed an alternative image-processing algorithm that requires minimal user interaction: an ultrafast algorithm that computes left ventricular ejection fraction (LVEF) by using temporal intensity variation in cine balanced steady-state free precession (bSSFP) short-axis images, with or without contrast medium. We evaluated the algorithm's performance against an expert observer's analysis for segmenting the LV cavity in 65 study participants (LVEF range, 12%-70%). In 12 instances, contrast medium was administered before cine imaging. Bland-Altman analysis revealed quantitative effects of LV basal, midcavity, and apical morphologic variation on the algorithm's accuracy. Total computation time for the LV stack was <2.5 seconds. The algorithm accurately delineated endocardial boundaries in 1,132 of 1,216 slices (93%). When contours in the extreme basal and apical slices were not adequate, they were replaced with manually drawn contours. The Bland-Altman mean differences were <1.2 mL (0.8%) for end-diastolic volume, <5 mL (6%) for end-systolic volume, and <3% for LVEF. Standard deviation of the difference was ≤4.1% of LV volume for all sections except the midcavity in end-systole (8.3% of end-systolic volume). We conclude that temporal intensity variation-based ultrafast LVEF computation is clinically accurate across a range of LV shapes and wall motions and is suitable for postcontrast cine SSFP imaging. Our algorithm enables real-time processing of cine bSSFP images on a commercial scanner console within 3 seconds in an unobtrusive automated process.

The Integration of a Lesson Study Model into Distance STEM Education during the COVID-19 Pandemic: Teachers’ Views and Practice

This paper investigated the integration of a Lesson Study Model (LSM) into distance STEM education during the COVID-19 pandemic. The study focused on six dimensions: (1) STEM education in distance learning, (2) Lesson Study (LS), (3) lesson planning processes, (4) challenges of lesson planning, (5) evaluation and assessment methods, and (6) strategies, methods, and techniques. The sample consisted of 24 science teachers recruited using criterion sampling, which is a purposive sampling method. A case study, which is a qualitative research method, was the design of choice. Data were collected through interviews, videotapes, and expert observations. The data were analyzed using inductive content analysis. Themes, categories, and codes were developed in accordance with the research purpose. Participants had positive opinions about the LSM, STEM education, and distance learning. Participants stated that the LSM activities within distance learning contributed to pedagogy and content knowledge in the STEM education process. The challenges faced by participants were unfavorable environmental conditions, time management issues, and a lack of knowledge and experience in lesson planning. Expert observations and videotapes corroborate these results, indicating that the LSM integrated with STEM education results in higher quality STEM lesson planning and teaching. Moreover, distance learning platforms are promising ways to ensure the professional development of teachers during the pandemic.

Kepemimpinan Kepala Sekolah dalam Peningkatan Mutu Pendidikan : Studi Kasus di SMK Nurul Jadid

The research is focused on the leadership of principals in improving the service and quality of NJ Vocational High Schools, with research questions directed at: What is the function and principals manner management in upgrading school quality and service in NJ Vocational Schools? What is the reality of quality and educational services currently at NJ Vocational School? To express questions, the method used by researchers is a qualitative method, by focus evidence analysis. To extract information and data from the informant (informant), the researcher used document analysis techniques, observation, and then ended with an interview to confirm the data. The results reveal that; Principal's leadership style in improving service and education quality in SMK Nurul Jadid Paiton Probolinggo is a team or democratic management style. Whereas the leadership function that is applied is in line with the concept of leadership which is widely raised by expert observers. The reality of schools quality in SMK Nurul Jadid Paiton Probolinggo, such as, raw inputs develop rapidly, the instrumental quality of inputs is incomplete but effective, and the environmental quality in the educational institutions is harmony.

METHODOLOGICAL FOUNDATIONS FOR BUILDING A MODEL OF COORDINATION FLOWS OF SYNERGY EFFECT FROM INTERACTIONS BETWEEN SUBJECTS OF THE MARKET OF INNOVATIVE TECHNOLOGIES

Topicality. Transformational changes in the era of building an intelligent society - Society 5.0, the emergence of "digital capitalism" in the world and the course taken by Ukraine towards digitalization in aggregate lead to a new organizational practice of entrepreneurship and economic management, where innovations in the field of science and technology will play a leading role in ensuring balanced economic development and solving social problems. The above has led to the intensification of activities related to the processing and dissemination of information in management structures, which has become an important area of work in economic research in Ukraine. This explains the need to take into account in practice the informational relationships between the subjects of management structures in the context of the digitalization of the Ukrainian economy and the coordination of their actions.Aim and tasks. The purpose of the article is to develop and substantiate the methodological foundations for constructing a model of coordination flows of synergistic effect from interaction between the subjects of the market of innovative technologies.Research results. The component base of construction of model of coordination streams of synergetic effect from interaction between subjects of the market of innovative technologies on the basis of economic synergetics and the theory of "soft" modeling on the following components is offered and substantiated; conceptual and categorical apparatus of modeling; conceptual approach to building a model of coordination flows to calculate the synergetic effect of the interaction between the subjects of the market of innovative technologies; elements of information interaction of participants of managerial relations; organizational and hierarchical structure of the model of coordination flows to calculate the synergetic effect of the interaction between the subjects of the market of innovative technologies.Conclusion. The model of coordination flows to calculate the synergetic effect of the interaction between the subjects of the market of innovative technologies is a three-tier management system, which has the main characteristics of multidimensional hierarchical systems. The range of information change varies from "0" to "1" and allows the selection of the information base to use the method of integrated assessment and expert observation. The main result of the decision according to this model is to obtain sufficient (optimal) quantity and quality of information by each management entity in the market of innovative technologies, which allows to formulate a general quasi-optimal solution facing the market of innovative technologies of Ukraine.This model is universal and can be used to analyze any information flows, as well as it is advisable to use in the construction of hybrid models of decision-making in the management of the processes of the market of innovative technologies.

Patient handover education programme based on situated learning theory for nursing students in clinical practice.

If not conducted correctly, nursing handover can threaten patient safety, and so nursing students require good handover education. This study evaluated a handover education programme based on situated learning theory in a clinical practicum. A quasi-experimental design and convenience sampling technique were used. The participants (fourth-grade nursing students recruited from a college in the C province of South Korea) were assigned to an intervention group (n = 38) or a control group (n = 39). A handover education programme that included lectures, expert observations, role playing, peer learning and reflection was received by the intervention group. The control group attended lectures and observed handovers. The handover skills of all participants were tested 2 weeks before and on the last day of the clinical practicum. Handover performance ability, handover clinical judgement ability and handover self-efficacy were outcome variables. Significant improvements in handover performance ability, handover clinical judgement ability and handover self-efficacy were observed in the intervention group compared with the control group. The significance of this study lies in the development and application of a programme based on situated learning theory for handover education. Application of theory-based handover education in clinical practicums is recommended to improve the handover capabilities of nursing students.

DETECTING APICAL RADIOLUCENCIES USING DEEP LEARNING TECHNOLOGY: A PILOT STUDY

<h3>BACKGROUND</h3> Dentists rely on radiographs in making treatment decisions every day. However, if inattentively read, radiographs can lead to over- or undertreatment. <h3>OBJECTIVE(S)</h3> The objectives were to assess the diagnostic performance of a deep learning algorithm at detecting apical radiolucencies (ARs) on intraoral (IO) radiographs and compare the performance of the algorithm vs interpretation by experts. <h3>STUDY DESIGN</h3> A search was conducted using the University of North Carolina cone beam computed tomography (CBCT) referral database for volumes acquired for endodontic evaluation. The inclusion criteria consisted of permanent teeth that exhibited apical radiolucencies measuring ≥2 mm on CBCT with a diagnostic IO radiograph for the same site. The exclusion criteria included patients under 18 years old and CBCT and IO images acquired more than 6 months apart. After applying the inclusion and exclusion criteria, 192 cases were found. The CBCT volumes served as ground truth for the IO radiograph annotation. The IO radiographs were randomly assigned to one of 3 groups: 6 images, observer calibration; 54 images, training the artificial intelligence (AI) algorithm; 132 images, testing set. Additionally, 132 IO radiographs with no evidence of apical radiolucencies were included to serve as controls. For this pilot, 70 images were randomly selected to create a testing subset derived from the main control and positive testing sets. Three experts were presented with this testing subset and asked to independently determine locations of AR and confidence of presence using a 5-point Likert scale. <h3>RESULTS</h3> The standalone software performance results by tooth were as follows: Sensitivity was 93%, specificity was 88%, and the area under the receiver operating characteristic curve (ROC-AUC) was 94% (95% confidence interval [CI], 89%, 98%). The combined results of the experts were as follows: sensitivity was 87%, specificity was 97%, and ROC-AUC was 93% (95% CI, 88%, 98%). Notably, the software performance metrics were lowest in the maxillary posterior region. <h3>DISCUSSION/CONCLUSIONS</h3> Using a limited testing data set, AI provided comparable performance to expert observers for this task. Further AI training is necessary to increase the sensitivity and specificity of AR detection in the posterior maxillary region.

Creating a Reading Culture in a Preschool in Collaboration with Children, Teachers and Parents

Adopting a reading culture is a process that takes shape in family starting from the moment the child is born and school environment. The most critical phase of this process is the “preschool period.” Therefore, the main purpose of this study is to construct a systematic intervention to create a reading culture in the preschool period. For this purpose, the study included “preschoolers, teachers, and parents” as the participants considering them as stakeholders in the process of building a reading culture. The population of the study is the preschools located in the district of Ereğli, Zonguldak, Turkey and the sample consists of 16 preschoolers at a preschool in Ereğli along with their parents (n=16) and their teachers (n=2). The study was carried out as an action research conducted for a period of 12 weeks. The 12-week intervention timeline is divided into two phases. In the first phase (first six weeks), the seminars on creating a reading culture were given to teachers and parents by a field expert and in-class observations of preschoolers were made. In the second phase, creative reading activities were implemented with the children (as two sections - A and B) for an hour once a week. The data come from observations, interviews, and participant diaries and were analyzed through content analysis. The study is considered to be crucial for the relevant literature as it includes children, teachers and parents, at the same time, as the three key stakeholders in the process of building a reading culture. At the end of the 12-week intervention, both positive and significant changes were observed both in children and parents as well as in teachers in terms of theoretical and practical aspects of adopting a reading culture.

Artificial intelligence in orthodontics: Where are we now? A scoping review.

This scoping review aims to determine the applications of Artificial Intelligence (AI) that are extensively employed in the field of Orthodontics, to evaluate its benefits, and to discuss its potential implications in this speciality. Recent decades have witnessed enormous changes in our profession. The arrival of new and more aesthetic options in orthodontic treatment, the transition to a fully digital workflow, the emergence of temporary anchorage devices and new imaging methods all provide both patients and professionals with a new focus in orthodontic care. This review was performed following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The electronic literature search was performed through MEDLINE/PubMed, Scopus, Web of Science, Cochrane and IEEE Xplore databases with a 11-year time restriction: January 2010 till March 2021. No additional manual searches were performed. The electronic literature search initially returned 311 records, and 115 after removing duplicate references. Finally, the application of the inclusion criteria resulted in 17 eligible publications in the qualitative synthesis review. The analysed studies demonstrated that Convolution Neural Networks can be used for the automatic detection of anatomical reference points on radiological images. In the growth and development research area, the Cervical Vertebral Maturation stage can be determined using an Artificial Neural Network model and obtain the same results as expert human observers. AI technology can also improve the diagnostic accuracy for orthodontic treatments, thereby helping the orthodontist work more accurately and efficiently.