A methodology based on quality gates for certifiable AI in medicine: towards a reliable application of metrics in machine learning

As of now, intelligent technologies experience a rapid growth. For a reliable adoption of those new and powerful systems into day-to-day life, especially with respect to high-risk settings such as medicine, technical means to realize legal requirements correctly, are indispensible. Our proposed methodology comprises an approach to translate such partly more abstract concepts into concrete instructions - it is based on Quality Gates along the intelligent system’s complete life cycle, which are composed of use-case adapted Criteria that need to be addressed with respect to certification. Also, the underlying philosophy regarding stakeholder inclusion, domain embedding and risk analysis is illustrated. In the present paper, the Quality Gate Metrics is outlined for the application of machine learning performance metrics focused on binary classification

Where to park? A behavioural comparison of bus Park and Ride and city centre car park usage in Bath, UK

Integrating car parking facilities with public transport in Park and Ride (P&R) facilities has the potential to shorten car trips, contributing to more sustainable mobility. There is an ongoing debate about the actual effects of P&R on the transport system at the subregional level. A key issue is the relative attractiveness of city centre car parks (CCCP), P&R and public transport. The paper presents the findings of a comparative empirical case-study based on a field survey of CCCP and P&R users conducted in the city of Bath, UK. Spatial and statistical analyses are applied. Radial distance to parking, availability of P&R sites in the direction of travel, gender, age, income and party-size are found to be important factors in a binary logistic regression model, explaining the revealed-preference of parking type. Stated analysis of foregone parking alternatives suggests more use of public transport and walking/cycling would likely occur without first-best parking alternatives. The policy implications and possible planning alternatives to P&R at the urban fringes for achieving greater sustainability goals are also discussed. © 2014 Elsevier Ltd

Immunohistochemical patterns in the differential diagnosis of rhinopharyngeal granulocytic sarcoma

Granulocytic sarcoma (GS) is a rare extramedullary manifestation of acute myeloid leukemia (AML). GS may develop simultaneously to AML or as a relapse of leukemia, particularly following allogeneic hematopoietic stem cell transplant. Subperiosteal bone, lymph nodes and skin are commonly involved, whereas rhinopharyngeal involvement is less common, with only 14 cases reported in the literature. Due to its rarity, rhinopharyngeal GS may lead to diagnostic pitfalls, particularly when it is poorly differentiated or is without concomitant marrow involvement. Thus, immunohistochemical findings play a key role in diagnosis. The current report describes a case of a 53-year-old female suffering from rhinopharyngeal GS and with a history of AML treated with chemotherapy and radiotherapy, focusing on the importance of the immunohistochemical pattern to assess the right diagnosis. Recent studies have demonstrated that the immunophenotype is of utmost importance for the diagnosis of GS. The high expression of myeloperoxidase (MPO) is common in GS; however, ~30% of GSs do not contain MPO. Therefore, the presence of other markers is required to confirm the diagnosis of GS

Strategy for the treatment and follow-up of sinonasal solitary extramedullary plasmacytoma: a case series

Extramedullary plasmacytoma is a rare neoplasm characterized by monoclonal proliferation of plasma cells outside bone marrow. It accounts for 4% of all non-epithelial sinonasal tumors. According to the literature, radiotherapy is the standard therapy for extramedullary plasmacytoma. However, the conversion rate of extramedullary plasmacytoma to multiple myeloma is reported to be between 11 and 33% over 10 years. The highest risk of conversion is reported during the first 2 years after diagnosis, but conversion has been noted up to 15 years after diagnosis. Once conversion to multiple myeloma is complete, less than 10% of patients will survive 10 years

Towards automated COVID-19 presence and severity classification

COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of intensive care units, predicting the future severity of a COVID-19 patient is crucial. The presented approach follows state-of-theart techniques to aid medical professionals in these situations. It comprises an ensemble learning strategy via 5-fold cross-validation that includes transfer learning and combines pre-trained 3D-versions of ResNet34 and DenseNet121 for COVID19 classification and severity prediction respectively. Further, domain-specific preprocessing was applied to optimize model performance. In addition, medical information like the infection-lung-ratio, patient age, and sex were included. The presented model achieves an AUC of 79.0% to predict COVID-19 severity, and 83.7% AUC to classify the presence of an infection, which is comparable with other currently popular methods. This approach is implemented using the AUCMEDI framework and relies on well-known network architectures to ensure robustness and reproducibility

LIFEDATA - a framework for traceable active learning projects

Active Learning has become a popular method for iteratively improving data-intensive Artificial Intelligence models. However, it often presents a significant challenge when dealing with large volumes of volatile data in projects, as with an Active Learning loop. This paper introduces LIFEDATA, a Python- based framework designed to assist developers in implementing Active Learning projects focusing on traceability. It supports seamless tracking of all artifacts, from data selection and labeling to model interpretation, thus promoting transparency throughout the entire model learning process and enhancing error debugging efficiency while ensuring experiment reproducibility. To showcase its applicability, we present two life science use cases. Moreover, the paper proposes an algorithm that combines query strategies to demonstrate LIFEDATA’s ability to reduce data labeling effort

Comentarios sobre Ventajas de los bloqueos periféricos frente a la epidural en el postoperatorio de PTR. Rev Electrón AnestesiaR 2009; Volumen 1 (4): 19

Comentarios al artículo M Sánchez. Ventajas de los bloqueos periféricos frente a la epidural en el postoperatorio de PTR. 1(4)18

Tratado de justicia restaurativa. Un enfoque integrador

Esta obra nos presenta a la Justicia Restaurativa desde la configuración del derecho penal y los procesos de la misma en el orden penitenciario, en las comunidades escolares, en la igualdad de género. Realzando así mismo la habiliades del facilitador que habrá de llevarla a cabo, como parte integral de un nuevo paradigma en la formación de recursos humnos que atiendan la inminente necesidad de este tipo de ejercicio y en las redes primarias de apoyo, como elemento restaurativo para las mujeres víctimas de violencia doméstica, dónde ha crecido la respuesta de la sociedad para abatir este sector de la violenci

Lentiviral Hematopoietic Stem Cell Gene Therapy Benefits Metachromatic Leukodystrophy

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