The maturity level of it management to support innovation within r&d centers in Brazil

Innovation is an important factor for R&D centers, it is the goal to be achieved in the development of technological projects. IT plays a fundamental role in this process. This paper seeks to understand the maturity level of IT management to support innovation within R&D centers in Brazil.Innovation is an important factor for R&D centers, it is the goal to be achieved in the development of technological projects. IT plays a fundamental role in this process. This paper seeks to understand the maturity level of IT management to support innovation within R&D centers in Brazil

Saliency-Enhanced Content-Based Image Retrieval for Diagnosis Support in Dermatology Consultation: Reader Study

BACKGROUND Previous research studies have demonstrated that medical content image retrieval can play an important role by assisting dermatologists in skin lesion diagnosis. However, current state-of-the-art approaches have not been adopted in routine consultation, partly due to the lack of interpretability limiting trust by clinical users. OBJECTIVE This study developed a new image retrieval architecture for polarized or dermoscopic imaging guided by interpretable saliency maps. This approach provides better feature extraction, leading to better quantitative retrieval performance as well as providing interpretability for an eventual real-world implementation. METHODS Content-based image retrieval (CBIR) algorithms rely on the comparison of image features embedded by convolutional neural network (CNN) against a labeled data set. Saliency maps are computer vision-interpretable methods that highlight the most relevant regions for the prediction made by a neural network. By introducing a fine-tuning stage that includes saliency maps to guide feature extraction, the accuracy of image retrieval is optimized. We refer to this approach as saliency-enhanced CBIR (SE-CBIR). A reader study was designed at the University Hospital Zurich Dermatology Clinic to evaluate SE-CBIR's retrieval accuracy as well as the impact of the participant's confidence on the diagnosis. RESULTS SE-CBIR improved the retrieval accuracy by 7% (77% vs 84%) when doing single-lesion retrieval against traditional CBIR. The reader study showed an overall increase in classification accuracy of 22% (62% vs 84%) when the participant is provided with SE-CBIR retrieved images. In addition, the overall confidence in the lesion's diagnosis increased by 24%. Finally, the use of SE-CBIR as a support tool helped the participants reduce the number of nonmelanoma lesions previously diagnosed as melanoma (overdiagnosis) by 53%. CONCLUSIONS SE-CBIR presents better retrieval accuracy compared to traditional CBIR CNN-based approaches. Furthermore, we have shown how these support tools can help dermatologists and residents improve diagnosis accuracy and confidence. Additionally, by introducing interpretable methods, we should expect increased acceptance and use of these tools in routine consultation

Saliency-Enhanced Content-Based Image Retrieval for Diagnosis Support in Dermatology Consultation: Reader Study.

BACKGROUND Previous research studies have demonstrated that medical content image retrieval can play an important role by assisting dermatologists in skin lesion diagnosis. However, current state-of-the-art approaches have not been adopted in routine consultation, partly due to the lack of interpretability limiting trust by clinical users. OBJECTIVE This study developed a new image retrieval architecture for polarized or dermoscopic imaging guided by interpretable saliency maps. This approach provides better feature extraction, leading to better quantitative retrieval performance as well as providing interpretability for an eventual real-world implementation. METHODS Content-based image retrieval (CBIR) algorithms rely on the comparison of image features embedded by convolutional neural network (CNN) against a labeled data set. Saliency maps are computer vision-interpretable methods that highlight the most relevant regions for the prediction made by a neural network. By introducing a fine-tuning stage that includes saliency maps to guide feature extraction, the accuracy of image retrieval is optimized. We refer to this approach as saliency-enhanced CBIR (SE-CBIR). A reader study was designed at the University Hospital Zurich Dermatology Clinic to evaluate SE-CBIR's retrieval accuracy as well as the impact of the participant's confidence on the diagnosis. RESULTS SE-CBIR improved the retrieval accuracy by 7% (77% vs 84%) when doing single-lesion retrieval against traditional CBIR. The reader study showed an overall increase in classification accuracy of 22% (62% vs 84%) when the participant is provided with SE-CBIR retrieved images. In addition, the overall confidence in the lesion's diagnosis increased by 24%. Finally, the use of SE-CBIR as a support tool helped the participants reduce the number of nonmelanoma lesions previously diagnosed as melanoma (overdiagnosis) by 53%. CONCLUSIONS SE-CBIR presents better retrieval accuracy compared to traditional CBIR CNN-based approaches. Furthermore, we have shown how these support tools can help dermatologists and residents improve diagnosis accuracy and confidence. Additionally, by introducing interpretable methods, we should expect increased acceptance and use of these tools in routine consultation

Reduced Rate of Hospital Admissions for ACS during Covid-19 Outbreak in Northern Italy

To address the coronavirus (Covid-19) pandemic,1 strict social containment measures have been adopted worldwide, and health care systems have been reorganized to cope with the enormous increase in the numbers of acutely ill patients.2,3 During this same period, some changes in the pattern of hospital admissions for other conditions have been noted. The aim of the present analysis is to investigate the rate of hospital admissions for acute coronary syndrome (ACS) during the early days of the Covid-19 outbreak

The maturity level of it management to support innovation within r&d centers in Brazil

Innovation is an important factor for R&D centers, it is the goal to be achieved in the development of technological projects. IT plays a fundamental role in this process. This paper seeks to understand the maturity level of IT management to support innovation within R&D centers in Brazil.Innovation is an important factor for R&D centers, it is the goal to be achieved in the development of technological projects. IT plays a fundamental role in this process. This paper seeks to understand the maturity level of IT management to support innovation within R&D centers in Brazil

Retrospective study 2005-2015 of all cases of fetal death occurred at 6523 gestational weeks, in Friusli Venezia Giulia, Italy

Background: Intrauterine fetal death (IUFD) is a tragic event and, despite efforts to reduce rates, its incidence remains difficult to reduce. The objective of the present study was to examine the etiological factors that contribute to the main causes and conditions associated with IUFD, over an 11-year period in a region of North-East Italy (Friuli Venezia Giulia) for which reliable data in available. Methods: Retrospective analysis of all 278 IUFD cases occurred between 2005 and 2015 in pregnancies with gestational age 65 23 weeks. Results: The incidence of IUFD was 2.8\u2030 live births. Of these, 30% were small for gestational age (SGA), with immigrant women being significantly over-represented. The share of SGA reached 35% in cases in which a maternal of fetal pathological condition was present, and dropped to 28% in the absence of associated pathology. In 78 pregnancies (28%) no pathology was recorded that could justify IUFD. Of all IUFDs, 11% occurred during labor, and 72% occurred at a gestational age above 30 weeks. Conclusion: The percentage of IUFD cases for which no possible cause can be identified is quite high. Only the adoption of evidence-based diagnostic protocols, with integrated immunologic, genetic and pathologic examinations, can help reduce this diagnostic gap, contributing to the prevention of future IUFDs

Asthma in patients admitted to emergency department for COVID-19: prevalence and risk of hospitalization

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