One Explanation Does Not Fit XIL

Current machine learning models produce outstanding results in many areas but, at the same time, suffer from shortcut learning and spurious correlations. To address such flaws, the explanatory interactive machine learning (XIL) framework has been proposed to revise a model by employing user feedback on a model's explanation. This work sheds light on the explanations used within this framework. In particular, we investigate simultaneous model revision through multiple explanation methods. To this end, we identified that \textit{one explanation does not fit XIL} and propose considering multiple ones when revising models via XIL

Methodische Bewertung von Originalartikeln zu Radiomics und Machine Learning für Outcome-Vorhersagen basierend auf der Positronen-Emissions-Tomografie (PET)

AIM Despite a vast number of articles on radiomics and machine learning in positron emission tomography (PET) imaging, clinical applicability remains limited, partly owing to poor methodological quality. We therefore systematically investigated the methodology described in publications on radiomics and machine learning for PET-based outcome prediction. METHODS A systematic search for original articles was run on PubMed. All articles were rated according to 17 criteria proposed by the authors. Criteria with >2 rating categories were binarized into "adequate" or "inadequate". The association between the number of "adequate" criteria per article and the date of publication was examined. RESULTS One hundred articles were identified (published between 07/2017 and 09/2023). The median proportion of articles per criterion that were rated "adequate" was 65% (range: 23-98%). Nineteen articles (19%) mentioned neither a test cohort nor cross-validation to separate training from testing. The median number of criteria with an "adequate" rating per article was 12.5 out of 17 (range, 4-17), and this did not increase with later dates of publication (Spearman's rho, 0.094; p = 0.35). In 22 articles (22%), less than half of the items were rated "adequate". Only 8% of articles published the source code, and 10% made the dataset openly available. CONCLUSION Among the articles investigated, methodological weaknesses have been identified, and the degree of compliance with recommendations on methodological quality and reporting shows potential for improvement. Better adherence to established guidelines could increase the clinical significance of radiomics and machine learning for PET-based outcome prediction and finally lead to the widespread use in routine clinical practice

Learning using Unselected Features (LUFe)

Feature selection has been studied in machine learning and data mining for many years, and is a valuable way to improve classification accuracy while reducing model complexity. Two main classes of feature selection methods - filter and wrapper - discard those features which are not selected, and do not consider them in the predictive model. We propose that these unselected features may instead be used as an additional source of information at train time. We describe a strategy called Learning using Unselected Features (LUFe) that allows selected and unselected features to serve different functions in classification. In this framework, selected features are used directly to set the decision boundary, and unselected features are utilised in a secondary role, with no additional cost at test time. Our empirical results on 49 textual datasets show that LUFe can improve classification performance in comparison with standard wrapper and filter feature selection

Case Report—Myonecrosis in Feedlot Cattle

This report describes an outbreak of disease in a Northwestern Iowa feedlot from January to March of 2001. The cattle had been received in the feedlot in July and August, 2000. Clinical signs included severe lameness, recumbency and death. Lameness was not apparent early in the outbreak and the initial diagnosis was central nervous disease. No infectious or toxic cause could be demonstrated. Due to poor performance, approximately a third of the heifers were held back after the main group was sold. Half of these poor performing heifers displayed visible stiffness. Myonecrosis was demonstrated by significantly elevated serum creatine kinase concentrations in visibly affected cattle as compared to visibly unaffected cattle. Histological lesions were confirmed in cardiac muscle but skeletal muscle was not examined. The cattle had been fed a predominantly corn diet with a liquid supplement containing vitamin E calculated at 12.5 IU/head per day until late in the feeding period, when they were switched to a dry supplement delivering 40 IU/head per day. Serum and liver vitamin E concentrations in sampled animals were below the normal range. Common limitations in field investigations include a failure to test un-affected animals to enable comparisons between groups, testing of animals after disease onset resulting in an inability to demonstrate a temporal relationship between the cause and effect, and small sample sizes. Our case-report suffers to some extent from all these factors; however we suspect that the myonecrosis likely occurred due to Vitamin E deficiency. This presumptive diagnosis is based on the combination of knowledge of vitamin E, creatine kinase, (CK) and Aspartate Amino Transferase (AST) values in the sampled cattle, clinical signs observed, elimination of other possible etiologies and supportive statistical analyses. Investigation of unexplained debilitation in feedlot cattle, especially when accompanied by lameness, should include evaluations of serum and/or liver vitamin E concentrations, serum (AST) and (CK) concentration, muscle histology, and ration vitamin E concentration

Developing and implementing an Einsteinian science curriculum from Years 3 to 10 : Part A Concepts, rationale and learning outcomes

There has been a growing realisation that school science curricula do not adequately reflect the revolutionary changes in our scientific understanding of the 20th century. This discrepancy between current school education and our modern scientific understanding has led to calls for the modernisation of the science curriculum. Although there have been attempts to introduce topics of Einsteinian physics (i.e., quantum physics and relativity) to school education, often at the secondary level, we still lack a seamless curriculum in which modern science concepts are gradually introduced in primary and middle schools. Guided by the Model of Educational Reconstruction and following a mixed-methods research design, the Einstein-First project aims to address this gap. Einstein-First has developed and implemented an Einsteinian curriculum from Years 3 to 10 (students aged 7- 16) that resolves the disconnect between science in schools and the modern world. This paper presents the concepts, rationale, and learning outcomes of the curriculum implementation in six Australian schools with 315 students across Years 3 to 10. Our findings lay the foundation for informed curriculum development towards a school education that can enhance students' understanding and appreciation of the fundamental concepts of modern science and its impact on our society

Traumatized Syrian Refugees with Ambiguous Loss: Predictors of Mental Distress

Refugees from war zones often have missing significant others. A loss without confirmation is described as an ambiguous loss. This physical absence with simultaneous mental persistence can be accompanied by economic, social or legal problems, boundary ambiguity (i.e., uncertainty about who belongs to the family system), and can have a negative impact on mental health. The aim of this study was to identify sociodemographic and loss-related predictors for prolonged grief, anxiety, depression, post-traumatic stress disorder (PTSD) and somatization in treatment-seeking Syrian refugees with post-traumatic stress symptoms in Germany experiencing ambiguous loss. For the present study, data were based on the treatment-seeking baseline sample of the “Sanadak” randomized-controlled trial, analyzing a subsample of 47 Syrian refugees with post-traumatic stress symptoms in Germany experiencing ambiguous loss. Sociodemographic and loss-related questions were applied, along with standardized instruments for symptoms of prolonged grief (ICG), anxiety (GAD-7), depression (PHQ-9), PTSD (PDS-5) and somatization (PHQ-15). Linear regression models were used to predict mental health outcomes. Having lost a close family member and higher boundary ambiguity showed a statistically significant association with higher severity in prolonged grief. The overall model for somatization reached statistical significance, while no predictor independently did. Boundary ambiguity showed a statistically significant positive association with depression, while the overall model showed no statistically significant associations. Boundary ambiguity and missing family members seemed to be important predictors for prolonged grief. These findings support the importance of reunification programs and suggest an inclusion of the topic into psychosocial support structures, e.g., including psychoeducational elements on boundary ambiguity in support groups for traumatized individuals and families experiencing ambiguous loss. Further research is needed for a more detailed understanding of the impact of ambiguous loss on refugee populations

Inflammation in metabolically healthy and metabolically abnormal adolescents: The HELENA study

On behalf of the HELENA study group.[Background and aims] Inflammation may influence the cardio-metabolic profile which relates with the risk of chronic diseases. This study aimed to assess the inflammatory status by metabolic health (MH)/body mass index (BMI) category and to assess how inflammatory markers can predict the cardio-metabolic profile in European adolescents, considering BMI. [Methods and results] A total of 659 adolescents (295 boys) from a cross-sectional European study were included. Adolescents were classified by metabolic health based on age- and sex-specific cut-off points for glucose, blood pressure, triglycerides, high density cholesterol and BMI. C-reactive protein (CRP), tumor necrosis factor alpha (TNF-α), interleukin (IL-6), complement factors (C3, C4) and cell adhesion molecules were assessed. [Results] Metabolically abnormal (MA) adolescents had higher values of C3 (p < 0.001) and C4 (p = 0.032) compared to those metabolically healthy (MHy). C3 concentrations significantly increased with the deterioration of the metabolic health and BMI (p < 0.001). Adolescents with higher values of CRP had higher probability of being in the overweight/obese-MH group than those allocated in other categories. Finally, high C3 and C4 concentrations increased the probability of having an unfavorable metabolic/BMI status. [Conclusions] Metabolic/BMI status and inflammatory biomarkers are associated, being the CRP, C3 and C4 the most related inflammatory markers with this condition. C3 and C4 were associated with the cardio-metabolic health consistently.The HELENA Study was supported by the European Community Sixth RTD Framework Programme (Contract FOOD-CT-2005-007034) and the Stockholm County Council. This analysis was also supported by the Spanish Ministry of Science and Innovation (JCI-2010-07055) and the gs4:European Regional Development Fund (FEDER). CCS is supported by the Spanish Ministry of Economy and Competitiveness (BES-2014-068829). FBO is supported by a grant from the Spanish Ministry of Science and Innovation (RYC-2011-09011). AIR was funded by a Juan de la Cierva-Formación stipend from the Ministry of Economy and Competitiveness of the Spanish Government (FJCI-2014-19795).Peer Reviewe