13 research outputs found
Impact of Airplane Crashes on Firm\u27s Credit Risk Under the CreditGrades Model
The paper examines the impact of airplane accidents with 40 or more fatalities, on airline\u27s firm credit risk. The sample contains 20 airplane crashes for the period 2000-2017. The analysis proposes the CreditGrades model introduced by Finger et al. (2002) , which is an extension of the first passage time model of Black and Cox (1976). The study concludes that airplane accidents lead to a statistically significant increase in airline\u27s Probability of Default. The results are both significant and robust under the t-Test and the non-parametric Wilcoxon Signed-rank test
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Identifying cardiomegaly in chest X-rays: a cross-sectional study of evaluation and comparison between different transfer learning methods
BACKGROUND: Cardiomegaly is a relatively common incidental finding on chest X-rays; if left untreated, it can result in significant complications. Using Artificial Intelligence for diagnosing cardiomegaly could be beneficial, as this pathology may be underreported, or overlooked, especially in busy or under-staffed settings.
PURPOSE: To explore the feasibility of applying four different transfer learning methods to identify the presence of cardiomegaly in chest X-rays and to compare their diagnostic performance using the radiologists' report as the gold standard.
MATERIAL AND METHODS: Two thousand chest X-rays were utilized in the current study: 1000 were normal and 1000 had confirmed cardiomegaly. Of these exams, 80% were used for training and 20% as a holdout test dataset. A total of 2048 deep features were extracted using Google's Inception V3, VGG16, VGG19, and SqueezeNet networks. A logistic regression algorithm optimized in regularization terms was used to classify chest X-rays into those with presence or absence of cardiomegaly.
RESULTS: Diagnostic accuracy is reported by means of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), with the VGG19 network providing the best values of sensitivity (84%), specificity (83%), PPV (83%), NPV (84%), and overall accuracy (84,5%). The other networks presented sensitivity at 64.1%-82%, specificity at 77.1%-81.1%, PPV at 74%-81.4%, NPV at 68%-82%, and overall accuracy at 71%-81.3%.
CONCLUSION: Deep learning using transfer learning methods based on VGG19 network can be used for the automatic detection of cardiomegaly on chest X-ray images. However, further validation and training of each method is required before application to clinical cases
The role of asset payouts in the estimation of default barriers
In the barrier option model of corporate security valuation, the firm’s creditors impose a default-triggering barrier on the firm value to protect their claim. Two disputed issues in the literature are whether the implied default barrier is positive, and whether it is above or below the book value of the firm’s liabilities. We extend the model of Brockman and Turtle (2003, Journal of Financial Economics 67, 511–529) by embedding asset payouts in the valuation of shareholders’ equity. Using a sample of US stocks from the NYSE, AMEX, and NASDAQ exchanges, our paper exploits market and firm information to compute the implied default barrier for thirty 2-digit SIC groups, including industrials and banks. Our results show that the implied default barrier is lower than it is in the received literature, and it can be less than total liabilities, even zero for some firms. The implied physical default probabilities are significantly lower in the presence of payouts, providing a closer fit to the historical corporate default rates, particularly for issuers of speculative-grade bonds
A cross-sectional study of explainable machine learning in Alzheimer’s disease: diagnostic classification using MR radiomic features
IntroductionAlzheimer’s disease (AD) even nowadays remains a complex neurodegenerative disease and its diagnosis relies mainly on cognitive tests which have many limitations. On the other hand, qualitative imaging will not provide an early diagnosis because the radiologist will perceive brain atrophy on a late disease stage. Therefore, the main objective of this study is to investigate the necessity of quantitative imaging in the assessment of AD by using machine learning (ML) methods. Nowadays, ML methods are used to address high dimensional data, integrate data from different sources, model the etiological and clinical heterogeneity, and discover new biomarkers in the assessment of AD.MethodsIn this study radiomic features from both entorhinal cortex and hippocampus were extracted from 194 normal controls (NC), 284 mild cognitive impairment (MCI) and 130 AD subjects. Texture analysis evaluates statistical properties of the image intensities which might represent changes in MRI image pixel intensity due to the pathophysiology of a disease. Therefore, this quantitative method could detect smaller-scale changes of neurodegeneration. Then the radiomics signatures extracted by texture analysis and baseline neuropsychological scales, were used to build an XGBoost integrated model which has been trained and integrated.ResultsThe model was explained by using the Shapley values produced by the SHAP (SHapley Additive exPlanations) method. XGBoost produced a f1-score of 0.949, 0.818, and 0.810 between NC vs. AD, MC vs. MCI, and MCI vs. AD, respectively.DiscussionThese directions have the potential to help to the earlier diagnosis and to a better manage of the disease progression and therefore, develop novel treatment strategies. This study clearly showed the importance of explainable ML approach in the assessment of AD
Valuation of European firms during the Russia-Ukraine war
We infer the asset value dynamics of European firms during the Russia-Ukraine war via the structural model of Merton (1974). Using high-frequency stock price data, we find that the war led to lower corporate security prices and higher asset volatility, eventually shifting asset values closer to the default region. On average, the balance sheet of European firms is expected to shrink by 2.05% and their 1-year default probability to increase from 0.32% to 2.12%. Regression analysis on asset and equity returns as well as default probability changes suggests that these effects are stronger for firms with large revenue exposure to Russia
Infliximab treatment in combination with cyclosporin A in patients with severe refractory rheumatoid arthritis
Materials and methods: Eighteen patients with refractory RA receiving low dose CsA (2 mg/kg/day) and prednisone (5 mg/day) were treated with intravenous infliximab. The patients were given infliximab (3 mg/kg weight) at 0, two, six, and every eight weeks thereafter for a total period of 12 months. Clinical improvement was evaluated according to the American College of Rheumatology (ACR) 20% response criteria. Results: Eighty per cent of patients receiving the combination treatment with CsA and infliximab achieved the 20% ACR criteria for response to treatment, whereas 39% satisfied the 50% response criteria. In addition, a 76% reduction in swollen and tender joint count was found. Finally, a reduction in C reactive protein and erythrocyte sedimentation rate was maintained throughout the study. In general, treatment was well tolerated, with minimal adverse drug reactions. Two patients dropped out; one because of an immediate hypersensitivity reaction and the other because of the development of pulmonary tuberculosis. Conclusion: Multiple infusions of infliximab and low doses of CsA improve patients with refractory RA. It seems that CsA may be an alternative disease modifying drug to be used in combination with infliximab in patients with refractory RA who cannot tolerate MTX
Infliximab therapy in patients with ankylosing spondylitis: an open label 12 month study
Patients and methods: Twenty five patients (24 male, 1 female; mean (SD) age 36.0 (10.5); disease duration 13.8 (8.5) years) with AS fulfilling the modified New York criteria for AS were investigated. Twenty two (88%) patients were HLA-B27 positive. All patients had active axial disease (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) ⩾30/100) and C reactive protein (CRP) ⩾10 mg/l, despite adequate treatment. Intravenous infliximab (5 mg/kg) was given at weeks 0, 2, 6, and every eight weeks thereafter for 12 months. The primary end point was the reduction of the patient's global assessment of pain (GAP) by >20% on a 100 mm visual analogue scale. Results: GAP was reduced by >20% in 23 (92%) patients, by 50% in 21 (84%) patients, and by 70% in 13 (52%). The change in BASDAI and CRP from baseline was statistically significant. The treatment was well tolerated with minimal side effects. One patient dropped out owing to inefficacy and one stopped treatment owing to an allergic reaction. Conclusion: This longer length study confirms the efficacy of infliximab and the good safety profile in patients with AS
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Exploring radiographers' perceptions and knowledge about patient lead shielding: a cross-sectional study in Greece and Cyprus
The present study aimed to explore radiographers' knowledge, clinical practice and perceptions regarding the use of patient lead shielding in Greece and Cyprus. Qualitative data were analyzed using conceptual content analysis and through the classification of findings into themes and categories. A total of 216 valid responses were received. Most respondents reported not being aware of the patient shielding recommendations issued by the American Association of Physicists in Medicine (67%) or the guidance issued by the British Institute of Radiology (69%). Shielding-related training was generally not provided by radiography departments (74%). Most of them (85%) reported that they need specific guidance on lead shielding practices. Also, 82% of the respondents said that lead shielding should continue to be used outside the pelvic area when imaging pregnant patients. Pediatric patients are the most common patient category to which lead shielding was applied. Significant gaps in relevant training have been identified among radiographers in Greece and Cyprus, highlighting the need for new protocols and provision of adequate training on lead shielding practices. Radiography departments should invest in appropriate shielding equipment and adequately train their staff
Linking Early Life Hypothalamic–Pituitary–Adrenal Axis Functioning, Brain Asymmetries, and Personality Traits in Dyslexia: An Informative Case Study
Developmental dyslexia (DD) is a multi-system disorder, combining influences of susceptibility genes and environmental factors. The causative interaction between specific genetic factors, brain regions, and personality/mental disorders, as well as specific learning disabilities, has been thoroughly investigated with regard to the approach of developing a multifaceted diagnostic procedure with an intervention strategy potential. In an attempt to add new translational evidence to the interconnection of the above factors in the occurrence of DD, we performed a combinatorial analysis of brain asymmetries, personality traits, cognitive and learning skills, and expression profiles of selected genes in an adult, early diagnosed with DD, and in his son of typical development. We focused on the expression of genes, based on the assumption that the regulation of transcription may be affected by genetic and epigenetic factors. The results highlighted a potential chain link between neuroplasticity-related as well as stress-related genes, such as BDNF, Sox4, mineralocorticoid receptor (MR), and GILZ, leftward asymmetries in the amygdala and selective cerebellum lobules, and tendencies for personality disorders and dyslexia. This correlation may reflect the presence of a specific neuro-epigenetic component of DD, ensuing from the continuous, multifaceted difficulties in the acquisition of cognitive and learning skills, which in turn may act as a fostering mechanism for the onset of long-term disorders. This is in line with recent findings demonstrating a dysfunction in processes supported by rapid neural adaptation in children and adults with dyslexia. Accordingly, the co-evaluation of all the above parameters may indicate a stress-related dyslexia endophenotype that should be carefully considered for a more integrated diagnosis and effective intervention. © Copyright © 2019 Zakopoulou, Vlaikou, Darsinou, Papadopoulou, Theodoridou, Papageorgiou, Alexiou, Bougias, Siafaka, Zoccolotti, Chroussos, Syrrou and Michaelidis