Validity Of Classification Research Articles

Determining whether false positive rates increase with performance validity test battery expansion

Objective Performance validity test (PVT) misclassification is an important concern for neuropsychologists. The present study determined whether expanding PVT analysis from 4-PVTs to 8-PVTs could lead to elevated rates of false positive performance validity misclassifications. Method Retrospective analysis of 443 patients who underwent a fixed neuropsychological test battery in a mixed clinical and forensic setting. Rates of failing two PVTs were compared to those predicted by Monte Carlo simulations when PVT analysis extended from 4-PVTs to 8-PVTs. Indeterminate performers (IDT; n = 42; those who failed two PVTs only after PVT analysis extended from 4-PVTs to 8-PVTs) were compared to a PVT-Fail group (n = 148; those who failed two PVTs in the 4-PVT battery or failed >2 PVTs). Results Rate of failing two PVTs remained stable when PVT analysis extended from 4- to 8-PVTs (12.9 to 11.9%) and was significantly lower than those predicted by Monte Carlo simulations. Compared to PVT-Fail, the IDT group was significantly younger, had stronger neuropsychological test performance, and demonstrated comparable rates of forensic referral and conditions with known neurocognitive sequelae (e.g. stroke, moderate-to-severe TBI). Conclusions Monte Carlo simulations significantly overestimated rates of individuals failing two PVTs as PVT battery length doubled. IDT did not differ from PVT-Fail across variables with known PVT effects (e.g. age, referral context, neurologic diagnoses), lowering concern that this group is comprised entirely of false-positive PVT classifications. More research is needed to determine the effect of PVT battery length on validity classification accuracy.

Defining and Verifying New Local Climate Zones with Three-Dimensional Built Environments and Urban Metabolism

The urban heat island (UHI) effect, where the temperature in an urban area is higher than in the surrounding rural areas, is becoming a major concern. The concept of a Local Climate Zone (LCZ) system was devised to provide an objective framework for UHI research, which allows for a microscale definition of the UHI effect within urban areas by considering ‘urban’ and ‘rural’ as a continuum versus a dichotomy. However, most LCZ types are classified only by surface structure and coverings, which seem irrelevant to climatological and microscale concepts. In addition, microclimate is influenced by urban metabolism related to human activities as well as structural effects, but the LCZ-classification system does not incorporate these functional concepts. Therefore, this study proposes a novel urban-classification system that addresses the limitations of the LCZ concept by quantifying structural and functional elements of the city at the pedestrian level using S-DoT sensors and semantic segmentation techniques. This study holds significance as it suggests a New-LCZ (N-LCZ) system to support the classification framework of highly valid urban types and follow-up studies related to the UHI. Moreover, the N-LCZ offers a regional urban-planning strategy for sustainable development through a more valid classification system.

Employment of MQ gas sensors for the classification of Cistus ladanifer essential oils

The chemical composition of essential oils (EOs) from Cistus ladanifer has a huge variability throughout the year, impacting the oil quality. Nowadays, EO analytic chemistry techniques, which are expensive and destroy the sample, are utilized to measure the chemical composition. In the paper, we propose a combination of low-cost sensors and machine learning based system. As low-cost sensors, seven gas sensors are combined to obtain up to 36 features. Regarding machine learning, 31 multiclass classification algorithms are applied. Data from sensors were collected for 33 samples of EO from Cistus ladanifer. The generated dataset was split into training and test datasets, with 75 % of the data for training. The datasets were created to ensure a homogeneous chemical composition distribution on both training and test datasets. There were three target chemical compounds: Alpha-pinene and Viridiflorol as individual compounds and Terpenic Hydrocarbons as a group of chemical compounds. The value of the percentage of each targeted compound is converted into a categoric variable with 5 possible values, 1 being the lowest concentration and 5 being the maximum one. The data of the MQ-sensors were included as the input for the models, and each one of the targeted chemical compounds was selected as an output for different models. The input features were ranged using different algorithms for the feature selection process. The results indicate that there is no valid classification model for Viridiflorol, and limited accuracy is achieved for Alpha-pinene. Meanwhile, for Terpenic Hydrocarbons, an accuracy of 91.6 % is achieved. It is important to highlight that these accuracies were attained when a reduced number of features were included, ranging the number of features from 11 to 13. This is the first case in which MQ-based gas sensors, or other metal oxide sensors, are used to correctly determine the concentration of a chemical compounds in a complex matrix formed by dozens of compounds. This system will provide a cheap method to determine the quality of EOs and confirm the benefits of combining low-cost sensors with machine learning.

Novel Loss-of-Function SYCP2 Variants in Infertile Males Upgrade the Gene-Disease Clinical Validity Classification for SYCP2 and Male Infertility to Strong.

Male infertility affects approximately 7% of the male population, and about 15% of these cases are predicted to have a genetic etiology. One gene implicated in autosomal dominant male infertility, SYCP2, encodes a protein critical for the synapsis of homologous chromosomes during meiosis I, resulting in impaired spermatogenesis. However, the clinical validity of the gene-disease pair was previously categorized as on the border of limited and moderate due to few reported cases. This study investigates the genetic cause of infertility for three unrelated Chinese patients with oligoasthenozoospermia. Whole exome sequencing (WES) and subsequent Sanger sequencing revealed novel heterozygous loss-of-function (LOF) variants in SYCP2 (c.89dup, c.946_947del, and c.4378_4379del). These cases, combined with the previously reported cases, provide strong genetic evidence supporting an autosomal dominant inheritance pattern. The experimental evidence also demonstrates a critical role for SYCP2 in spermatogenesis. Collectively, this updated assessment of the genetic and experimental evidence upgrades the gene-disease association strength of SYCP2 and autosomal dominant male infertility from on the border of limited and moderate to strong. The reclassification improves SYCP2 variant interpretation and qualifies it for the inclusion on diagnostic male infertility gene panels and prioritization in whole exome or genome studies for related phenotypes. These findings therefore improve the clinical interpretation of SYCP2 LOF variants.

X-Ray Source Classification Using Machine Learning: A Study with EP-WXT Pathfinder LEIA

X-ray observations play a crucial role in time-domain astronomy. The Einstein Probe (EP), a recently launched X-ray astronomical satellite, emerges as a forefront player in the field of time-domain astronomy and high-energy astrophysics. With a focus on systematic surveys in the soft X-ray band, EP aims to discover high-energy transients and monitor variable sources in the universe. To achieve these objectives, a quick and reliable classification of observed sources is essential. In this study, we developed a machine learning classifier for autonomous source classification using data from the EP-WXT Pathfinder—Lobster Eye Imager for Astronomy (LEIA) and EP-WXT simulations. The proposed Random Forest classifier, built on selected features derived from light curves, energy spectra, and location information, achieves an accuracy of approximately 95% on EP simulation data and 98% on LEIA observational data. The classifier is integrated into the LEIA data processing pipeline, serving as a tool for manual validation and rapid classification during observations. This paper presents an efficient method for the classification of X-ray sources based on single observations, along with implications of most effective features for the task. This work facilitates rapid source classification for the EP mission and also provides valuable insights into feature selection and classification techniques for enhancing the efficiency and accuracy of X-ray source classification that can be adapted to other X-ray telescope data.

Trauma-related preventable death; data analysis and panel review at a level 1 trauma centre in Amsterdam, the Netherlands.

Trauma-related death is used as a parameter to evaluate the quality of trauma care and identify cases in which mortality could have been prevented under optimal trauma care conditions. The aim of this study was to identify trauma-related preventable death (TRPD) within our institute by an external expert panel and to evaluate inter-panel reliability. Trauma-related deaths between the 1st of January 2020 and the 1st of February 2022 at the Amsterdam University Medical Centre were identified. The severely injured patients (injury severity score ≥ 16) were enrolled for preventability analysis by an external multidisciplinary panel, consisting of a trauma surgeon, anaesthesiologist, emergency physician, neurosurgeon, and forensic physician. Case descriptions were provided, and panellists were asked to classify deaths as non-preventable, potentially preventable, and preventable. Agreements between the five observers were assessed by Fleiss kappa statistics. In total 95 trauma-related deaths were identified. Of which 36 fatalities were included for analysis, the mean age was 55.3 years (± 24.5), 69.4% were male and 88.9% suffered blunt trauma. The mean injury severity score was 35.3 (± 15.3). Interobserver agreement within the external panel was moderate for survivability (Fleiss kappa 0.474) but low for categorical preventable death classification (Fleiss kappa 0.298). Most of the disagreements were between non-preventable or potentially preventable with care that could have been improved. Multidisciplinary panel review has a moderate inter-observer agreement regarding survivability and low agreement regarding categorical preventable death classification. A valid definition and classification of TRPD is required to improve inter-observer agreement and quality of trauma care.

The classification accuracy of Warrington’s recognition memory test (words) as a performance validity Test in a neurorehabilitation setting

This study was designed to evaluate the classification accuracy of the Warrington’s Recognition Memory Test (RMT) in 167 patients (97 or 58.1% men; M Age = 40.4; M Education= 13.8) medically referred for neuropsychological evaluation against five psychometrically defined criterion groups. At the optimal cutoff (≤42), the RMT produced an acceptable combination of sensitivity (.36-.60) and specificity (.85-.95), correctly classifying 68.4-83.3% of the sample. Making the cutoff more conservative (≤41) improved specificity (.88-.95) at the expense of sensitivity (.30-.60). Lowering the cutoff to ≤40 achieved uniformly high specificity (.91-.95) but diminished sensitivity (.27-.48). RMT scores were unrelated to lateral dominance, education, or gender. The RMT was sensitive to a three-way classification of performance validity (Pass/Borderline/Fail), further demonstrating its discriminant power. Despite a notable decline in research studies focused on its classification accuracy within the last decade, the RMT remains an effective free-standing PVT that is robust to demographic variables. Relatively low sensitivity is its main liability. Further research is needed on its cross-cultural validity (sensitivity to limited English proficiency).

Effect of processing speed and memory performance on classification accuracy of the dot counting test in a mixed neuropsychiatric sample

ABSTRACT Objective This study examined the impact of impairment in two specific cognitive abilities, processing speed and memory, on Dot Counting Test (DCT) classification accuracy by evaluating performance validity classification accuracy across cognitively unimpaired, single-domain impairment, and multidomain impairment subgroups within a mixed clinical sample. Method Cross-sectional data were analyzed from 348 adult outpatients classified as valid (n = 284) or invalid (n = 64) based on four independent criterion performance validity tests (PVTs). Unimpaired (n = 164), single-domain processing speed impairment (n = 24), single-domain memory impairment (n = 53), and multidomain processing speed and memory impairment (n = 43) clinical subgroups were established among the valid group. Both the traditional DCT E-score and unrounded E-score were examined. Results Overall, the DCT demonstrated acceptable to excellent classification accuracy across the unimpaired (area under the curve [AUC] traditional E-score=.855; unrounded E-score=.855) and single-domain impairment groups (traditional E-score AUCs = .690–.754; unrounded E-score AUCs = .692–747). However, it did not reliably discriminate the multidomain processing speed and memory impairment group from the invalid performers (traditional and unrounded E-scores AUC = .557). Conclusions Findings support the DCT as a non-memory-based freestanding PVT for use with single-domain cognitive impairment, with traditional E-score ≥17 (unrounded E-score ≥16.95) recommended for those with memory impairment and traditional E-score ≥19 (unrounded ≥18.08) with processing speed impairment. Moreover, results replicated previously established optimal cutoffs for unimpaired groups using both the traditional (≥14) and unrounded (≥13.84) E-scores. However, the DCT did not reliably discriminate between invalid performance and multidomain cognitive impairment, indicating caution is warranted when using the DCT with patients suspected of greater cognitive impairment.

Gait classification for growing children with Duchenne muscular dystrophy

Classifying gait patterns into homogeneous groups could enhance communication among healthcare providers, clinical decision making and clinical trial designs in boys with Duchenne muscular dystrophy (DMD). Sutherland’s classification has been developed 40 years ago. Ever since, the state-of-the-art medical care has improved and boys with DMD are now longer ambulatory. Therefore, the gait classification requires an update. The overall aim was to develop an up-to-date, valid DMD gait classification. A total of 137 three-dimensional gait analysis sessions were collected in 30 boys with DMD, aged 4.6–17 years. Three classes were distinguished, which only partly aligned with increasing severity of gait deviations. Apart from the mildly affected pattern, two more severely affected gait patterns were found, namely the tiptoeing pattern and the flexion pattern with distinct anterior pelvic tilt and posterior trunk leaning, which showed most severe deviations at the ankle or at the proximal segments/joints, respectively. The agreement between Sutherland’s and the current classification was low, suggesting that gait pathology with the current state-of-the-art medical care has changed. However, overlap between classes, especially between the two more affected classes, highlights the complexity of the continuous gait changes. Therefore, caution is required when classifying individual boys with DMD into classes.

Comprehensive molecular classification predicted microenvironment profiles and therapy response for HCC.

Tumor microenvironment (TME) heterogeneity leads to a discrepancy in survival prognosis and clinical treatment response for patients with HCC. The clinical applications of documented molecular subtypes are constrained by several issues. We integrated 3 single-cell data sets to describe the TME landscape and identified 6 prognosis-related cell subclusters. Unsupervised clustering of subcluster-specific markers was performed to generate transcriptomic subtypes. The predictive value of these molecular subtypes for prognosis and treatment response was explored in multiple external HCC cohorts and the Xiangya HCC cohort. TME features were estimated using single-cell immune repertoire sequencing, mass cytometry, and multiplex immunofluorescence. The prognosis-related score was constructed based on a machine-learning algorithm. Comprehensive single-cell analysis described TME heterogeneity in HCC. The 5 transcriptomic subtypes possessed different clinical prognoses, stemness characteristics, immune landscapes, and therapeutic responses. Class 1 exhibited an inflamed phenotype with better clinical outcomes, while classes 2 and 4 were characterized by a lack of T-cell infiltration. Classes 5 and 3 indicated an inhibitory tumor immune microenvironment. Analysis of multiple therapeutic cohorts suggested that classes 5 and 3 were sensitive to immune checkpoint blockade and targeted therapy, whereas classes 1 and 2 were more responsive to transcatheter arterial chemoembolization treatment. Class 4 displayed resistance to all conventional HCC therapies. Four potential therapeutic agents and 4 targets were further identified for high prognosis-related score patients with HCC. Our study generated a clinically valid molecular classification to guide precision medicine in patients with HCC.

A Multilevel Classification of Căluș Tunes (Argeș County)

The Ethnomusicological Study of Căluș Dances became part of the research plan of the Institute of Ethnography and Folklore “Constantin Brăiloiu”. The analysed corpus of the Călușul in Argeș consists of 200 tunes recorded by ethno-choreologist Anca Giurchescu, as direct observation or as re-enactment, and fully transcribed. In order to obtain a valid classification, we considered that the analysing terms should gather pieces with common features. Accordingly, we selected three coalescing parameters for defining the characteristics of this repertoire. This analysis led to a classification with 12 categories, infra-classes, which can be gradually grouped in sub-classes and, at a superior level, in classes. The special feature of our approach resides in the fact that these are interchangeable, which allows alternative multilevel classifications, in any necessary order. We consider that the analytical potential of the alternative multi-level classification is significant in highlighting the system of preferential relations created between hythmic, architectonic and melodic structures at the level of the entire repertoire. Keywords: rhythmic, architectonic, melodic level, multilevel classification.

Gross motor proficiency deficits among children and adolescents post posterior fossa brain tumor removal vs. traumatic brain injury in the chronic phase of recovery: a cross-sectional study.

Acquired brain injury (ABI) is a prevalent diagnosis in pediatric rehabilitation. Gross motor skills are often affected by ABI and limit the ability to participate in various physical activities. However, as ABI injury location is diverse, children and adolescents (youth) with localized ABI, such as ABI in the posterior fossa (ABI-PF) may present unique and different motor disabilities than youth with ABI on account of traumatic brain injury (TBI). The aims of the study were: (1) to compare gross motor deficits in youth with TBI vs. ABI-PF; and (2) to compare two methods on scoring BOT2 to determine which is better for identifying motor deficits. Participated in this study youth with TBI (N = 50) and ABI-PF (N = 30). Participants were tested on Bruininks-Oseretsky Test of Motor Proficiency-2nd Edition (BOT2) Upper-Limb Coordination, Balance, Strength, Running Speed and Agility, and Bilateral-Coordination subtests. Motor performance deficits were established using two-standard deviations (2SD) and age-equivalent methods. Between-group differences were assessed via independent t-tests and receiver operating characteristic curves (ROC). According to the 2SD method, motor deficits in the ABI-PF group ranged from 20% to 66.66%, whereas in the TBI group 8%-16%. According to the age-equivalent method, in the TBI and ABI-PF groups 40%-66.0% and 46.66%-76.66% of the youth presented motor deficits, respectively. Moreover, ROC analysis showed that motor performance deficits of both groups in all sub-scales except for Bilateral Coordination differed enough to result in medium area under the curve. Motor deficits post-pediatric ABI are prevalent. In comparison to the TBI group, deficits are greater in the ABI-PF group. Moreover, compared to the 2SD method, the extent of motor deficiency is greater in the age-equivalent method. Therefore, using the later might provide a more valid classification of deficits in gross motor proficiency for youth post-ABI.

A Modified and Refined Classification System for Secondary Cleft Nasolabial Deformities.

Secondary cleft lip (CL) deformities are commonly encountered in cleft management. Various attempts have been made to create a classification system that can comprehensively encapsulate residual CL deformities after primary repair. The aim of this study is to reinforce valid classification systems and to introduce a new classification subtype (Type V Revision). A longitudinal retrospective analysis was done in 35 outreach programs in 4 countries (Ecuador, Lebanon, Peru, and El Salvador) between 2015 and 2023. Two hundred sixty-nine patients, between the ages of 9 months and 45 years, with residual CL deformities after primary lip repair, were classified into one of the 5 classification types. Patients with syndromes were excluded from the study. Patients received one of 5 revision types depending on their initial preoperative evaluation and intraoperative analysis of anatomic involvement. The mean age at surgery was 12.86 years. Twenty-five patients received type I revision, 29 patients received type II revision, 81 patients received type III revision, 106 patients received type IV revision, and 28 patients received type V revision. As the surgical complexity advanced from type I to V, there was a gradual increase in the average surgical time. The Congruence between preoperative and postoperative revision types was substantial. Residual CL defects cause a significant burden on both the patient and cleft care provider. This classification system, with the newly introduced type V revision, enhances and eases the categorization and management of secondary CL deformities.

Rapid Grapevine Health Diagnosis Based on Digital Imaging and Deep Learning.

Deep learning plays a vital role in precise grapevine disease detection, yet practical applications for farmer assistance are scarce despite promising results. The objective of this research is to develop an intelligent approach, supported by user-friendly, open-source software named AI GrapeCare (Version 1, created by Osama Elsherbiny). This approach utilizes RGB imagery and hybrid deep networks for the detection and prevention of grapevine diseases. Exploring the optimal deep learning architecture involved combining convolutional neural networks (CNNs), long short-term memory (LSTM), deep neural networks (DNNs), and transfer learning networks (including VGG16, VGG19, ResNet50, and ResNet101V2). A gray level co-occurrence matrix (GLCM) was employed to measure the textural characteristics. The plant disease detection platform (PDD) created a dataset of real-life grape leaf images from vineyards to improve plant disease identification. A data augmentation technique was applied to address the issue of limited images. Subsequently, the augmented dataset was used to train the models and enhance their capability to accurately identify and classify plant diseases in real-world scenarios. The analyzed outcomes indicated that the combined CNNRGB-LSTMGLCM deep network, based on the VGG16 pretrained network and data augmentation, outperformed the separate deep network and nonaugmented version features. Its validation accuracy, classification precision, recall, and F-measure are all 96.6%, with a 93.4% intersection over union and a loss of 0.123. Furthermore, the software developed through the proposed approach holds great promise as a rapid tool for diagnosing grapevine diseases in less than one minute. The framework of the study shows potential for future expansion to include various types of trees. This capability can assist farmers in early detection of tree diseases, enabling them to implement preventive measures.

A review of the directly sampled endometrial cytology on LBC samples: Classification, microscopic criteria and beyond.

The Yokohama System for Reporting Endometrial Cytology (TYS) has been proposed by an expert meeting under the auspices of the International Academy of Cytology (IAC) in May 2016 at the IAC in Yokohama. Since its introduction, the TYS has been receiving worldwide acceptance, and this review aims to assess its global impact. The adoption of endometrial cytology as a diagnostic procedure has been hampered in the past by difficulties arising in interpreting the cellular findings due to a number of factors (such as excess blood, cellular overlapping and the complex physiology of endometrium). Recently, the use of liquid-based cytology (LBC), with its ability to remove blood and mucus and to distribute cells uniformly in a thin layer on the slide, has provided an opportunity to re-evaluate the role of endometrial cytology. LBC is a useful tool in the cytologic diagnosis and follow-up of endometrial abnormalities, which remains complementary to the emerging molecular diagnostic cytopathology. The study of LBC from endometrial cytology could be challenging since it is affected by numerous look-alikes and diagnostic pitfalls. This review discusses these various entities and takes into consideration the ancillary techniques that may be useful in the diagnostic procedure. In conclusion, our review of the published data suggests that the TYS is a valid classification scheme that has been widely accepted by cytopathologists globally, is highly reproducible and makes a valuable contribution to clinical therapeutic management. At present, molecular cytopathology is a rapidly evolving field of modern cytopathology, which underlines the effective interplay between genomics and cytology. This review aims to provide a comprehensive review of the drawbacks of endometrial cytopathology, particularly in terms of endometrial cancer diagnosis and molecular testing.

Assessment of safety risk in airline operations based on constant-sum game

Safety is the key to airline operations. The premise for ensuring safety is valid classification and scientific assessment of hazardous sources. The airlines, however, are deficient in an overall mastery and effective analysis of the hazardous sources currently. Here, we propose a model for a safety risk assessment in airline operations based on constant-sum games, with a comprehensive analysis of hazardous sources identified by airlines. The subjective and objective weights of the hazardous source indicators are balanced depending on the optimal coefficients, which are determined by deriving the countermeasure model through the constant-sum game theory. The comparative analysis of safety risks and weaknesses in management for airlines or secondary departments is then conducted. Meanwhile, a long-term reward mechanism is introduced into the model to eliminate the negative effect of a sudden increase in safety risk indices caused by the newly added hazardous sources. This method provides airlines with an accurate assessment of the safety status and an estimation of safety development which trends to make targeted decisions and realize prevention beforehand.

E-MODULE DEVELOPMENT IN ELECTRICAL CIRCUITS COURSES BASED ON PROJECT LEARNING

The lack of maximum learning motivation has a direct impact on student lecture out-comes. The provision of teaching modules needs to be adjusted to ICT developments in order to provide more meaningful lectures. This development research aims to produce e-modules based on project learning (PjBL) in electrical circuit courses that are valid, practi-cal and have a positive impact on student learning outcomes. This research is development research using the ADDIE model with five stages: analysis, design, development, imple-mentation, and evaluation. The subjects of this study consisted of 2 material, media, lan-guage experts, 38 semester 2 students, and 2 course lecturers. Data was collected through questionnaires and tests. The research instruments included validity and practicality ques-tionnaire sheets, as well as tests of electrical circuit lecture results. The results of the re-search show that the E-module developed has a validity level from media experts of 90.00% with a Very Valid classification, a validity level from language experts of 86.00% with a Very Valid classification, and a validity level from material experts of 92.00 % with Very Valid classification. This PjBL-based e-module also has a level of practicality in terms of the student aspect of 88.14%, including in the "Very Practical" category, a level of practicality in terms of the lecturer's aspect of 82.60%, including in the "Very Practical" category and is effective in improving results Electric circuit lecture.

J-PLUS: galaxy-star-quasar classification for DR3

ABSTRACT The Javalambre Photometric Local Universe Survey (J-PLUS) is a 12-band photometric survey using the 83-cm JAST telescope. Data Release 3 includes 47.4 million sources. J-PLUS DR3 only provides star-galaxy classification so that quasars are not identified from the other sources. Given the size of the data set, machine learning methods could provide a valid alternative classification and a solution to the classification of quasars. Our objective is to classify J-PLUS DR3 sources into galaxies, stars, and quasars, outperforming the available classifiers in each class. We use an automated machine learning tool called TPOT to find an optimized pipeline to perform the classification. The supervised machine learning algorithms are trained on the crossmatch with SDSS DR18, LAMOST DR8, and Gaia. We checked that the training set of about 660 thousand galaxies, 1.2 million stars, and 270 thousand quasars is both representative and contain a minimal presence of contaminants (less than 1 per cent). We considered 37 features: the 12 photometric bands with respective errors, 6 colours, 4 morphological parameters, galactic extinction with its error, and the PSF relative to the corresponding pointing. With TPOT genetic algorithm, we found that XGBoost provides the best performance: the AUC for galaxies, stars, and quasars is above 0.99 and the average precision is above 0.99 for galaxies and stars and 0.96 for quasars. XGBoost outperforms the classifiers already provided in J-PLUS DR3 and also classifies quasars.

A Novel Comprehensive Classification for Non-Prosthetic Peri-Implant Fractures

Non-prosthetic peri-implant fractures (NPPIFs) are often reported mixed with periprosthetic fractures (PPFs), but they are different entities. Due to the increase in the age of the world’s population and to the intensification of surgeries for fractures, nowadays, peri-implant fractures are a very frequent entity in clinical practice, with an increasing trend expected in the future. A clear exclusive classification of NPPIFs is not reported in the literature. The aim of this study is to provide a valid comprehensive classification for all the NPPIFs. X-rays of all the peri-implant cases treated in our unit in a 3-year period were retrospectively collected. Five orthopedic surgeons reviewed 30 X-rays of NPPIFs, providing a code according to the classification proposed. After a 3-month interval, they reviewed the same X-rays. Eighteen femoral, eight humeral, and four forearm peri-implant fractures were collected and showed to the raters. Inter- and intra-observer reliability was calculated using a k-statistic, showing a moderate agreement between observers (κ = 0.73) and a substantial agreement between the observations of the same viewer (κ = 0.82). The literature lacks a comprehensive classification for peri-implant fractures that considers all the bones and all the types of implants. The proposed classification is meant to be an instrument for orthopedic surgeons to categorize these types of fractures and seems to be simple, easy to comprehend, and reproducible. This new classification can provide the orthopedic surgeon a reliable method to clearly catalogue different fractures according to the site and the implants; the physicians can use it, through a code, in clinical practice to describe an NPPIF without the need of images. Further studies may be necessary to confirm the validity and eventually to improve the suggested classification.

Cluster analysis of multiple impairment measures in evidence-based classification for para-alpine sit skiers.

The International Paralympic Committee has been promoting the development of evidence-based classification to reduce the subjectivity in current decision-making systems. The current study aimed to evaluate the validity of the impairment and performance tests for para-alpine sit skiing classification, and whether cluster analysis of the measures would produce a valid classification structure. Thirty-eight para-alpine sit skiers with different disabilities completed seven tests. During these tests, isometric trunk strength, trunk muscle excitation, trunk range of movement (ROM), and simulated skiing performance (board tilt angle) were assessed. Correlations between the measures and the board tilt angle were calculated. To group athletes, K-means cluster analysis was performed according to how much the impairment measures affected the board tilting. There were significant correlations between all measures and the maximal board tilt angle (r = 0.35-0.81, p < 0.05). The cluster analysis revealed that the introduction of ROM and muscle excitation was an effective supplement to strength measures in improving the classification accuracy (53%-79%). It produced four clusters with strong structures (mean silhouette coefficient = 0.81) and large and significant inter-cluster differences in most measures and performance between clusters (p < 0.05). The cluster analysis produced classes comprising athletes with similar degrees of activity limitation. All tests reported can help establish a more transparent classification system for para-alpine sit skiers. This study also provides a reference for evidence-based classification systems in other Para sports.