|
Records |
Links |
|
Author |
Guillermo Torres; Sonia Baeza; Carles Sanchez; Ignasi Guasch; Antoni Rosell; Debora Gil |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
|
|
Title |
An Intelligent Radiomic Approach for Lung Cancer Screening |
Type |
Journal Article |
|
Year |
2022 |
Publication |
Applied Sciences |
Abbreviated Journal |
APPLSCI |
|
|
Volume |
12 |
Issue |
3 |
Pages |
1568 |
|
|
Keywords |
Lung cancer; Early diagnosis; Screening; Neural networks; Image embedding; Architecture optimization |
|
|
Abstract ![sorted by Abstract field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
The efficiency of lung cancer screening for reducing mortality is hindered by the high rate of false positives. Artificial intelligence applied to radiomics could help to early discard benign cases from the analysis of CT scans. The available amount of data and the fact that benign cases are a minority, constitutes a main challenge for the successful use of state of the art methods (like deep learning), which can be biased, over-fitted and lack of clinical reproducibility. We present an hybrid approach combining the potential of radiomic features to characterize nodules in CT scans and the generalization of the feed forward networks. In order to obtain maximal reproducibility with minimal training data, we propose an embedding of nodules based on the statistical significance of radiomic features for malignancy detection. This representation space of lesions is the input to a feed
forward network, which architecture and hyperparameters are optimized using own-defined metrics of the diagnostic power of the whole system. Results of the best model on an independent set of patients achieve 100% of sensitivity and 83% of specificity (AUC = 0.94) for malignancy detection. |
|
|
Address |
Jan 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; 600.139; 600.145 |
Approved |
no |
|
|
Call Number |
Admin @ si @ TBS2022 |
Serial |
3699 |
|
Permanent link to this record |
|
|
|
|
Author |
Miquel Angel Piera; Jose Luis Muñoz; Debora Gil; Gonzalo Martin; Jordi Manzano |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
|
|
Title |
A Socio-Technical Simulation Model for the Design of the Future Single Pilot Cockpit: An Opportunity to Improve Pilot Performance |
Type |
Journal Article |
|
Year |
2022 |
Publication |
IEEE Access |
Abbreviated Journal |
ACCESS |
|
|
Volume |
10 |
Issue |
|
Pages |
22330-22343 |
|
|
Keywords |
Human factors ; Performance evaluation ; Simulation; Sociotechnical systems ; System performance |
|
|
Abstract ![sorted by Abstract field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
The future deployment of single pilot operations must be supported by new cockpit computer services. Such services require an adaptive context-aware integration of technical functionalities with the concurrent tasks that a pilot must deal with. Advanced artificial intelligence supporting services and improved communication capabilities are the key enabling technologies that will render future cockpits more integrated with the present digitalized air traffic management system. However, an issue in the integration of such technologies is the lack of socio-technical analysis in the design of these teaming mechanisms. A key factor in determining how and when a service support should be provided is the dynamic evolution of pilot workload. This paper investigates how the socio-technical model-based systems engineering approach paves the way for the design of a digital assistant framework by formalizing this workload. The model was validated in an Airbus A-320 cockpit simulator, and the results confirmed the degraded pilot behavioral model and the performance impact according to different contextual flight deck information. This study contributes to practical knowledge for designing human-machine task-sharing systems. |
|
|
Address |
Feb 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; |
Approved |
no |
|
|
Call Number |
Admin @ si @ PMG2022 |
Serial |
3697 |
|
Permanent link to this record |
|
|
|
|
Author |
David Roche; Debora Gil; Jesus Giraldo |
![goto web page url](http://refbase.cvc.uab.es/img/www.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Multiple active receptor conformation, agonist efficacy and maximum effect of the system: the conformation-based operational model of agonism, |
Type |
Journal Article |
|
Year |
2013 |
Publication |
Drug Discovery Today |
Abbreviated Journal |
DDT |
|
|
Volume |
18 |
Issue |
7-8 |
Pages |
365-371 |
|
|
Keywords |
|
|
|
Abstract ![sorted by Abstract field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
The operational model of agonism assumes that the maximum effect a particular receptor system can achieve (the Em parameter) is fixed. Em estimates are above but close to the asymptotic maximum effects of endogenous agonists. The concept of Em is contradicted by superagonists and those positive allosteric modulators that significantly increase the maximum effect of endogenous agonists. An extension of the operational model is proposed that assumes that the Em parameter does not necessarily have a single value for a receptor system but has multiple values associated to multiple active receptor conformations. The model provides a mechanistic link between active receptor conformation and agonist efficacy, which can be useful for the analysis of agonist response under different receptor scenarios. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Elsevier |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; 600.057; 600.054 |
Approved |
no |
|
|
Call Number |
IAM @ iam @ RGG2013a |
Serial |
2190 |
|
Permanent link to this record |
|
|
|
|
Author |
Josep Llados; Enric Marti; Juan J.Villanueva |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
|
|
Title |
Symbol recognition by error-tolerant subgraph matching between region adjacency graphs |
Type |
Journal Article |
|
Year |
2001 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
|
|
|
Volume |
23 |
Issue |
10 |
Pages |
1137-1143 |
|
|
Keywords |
|
|
|
Abstract ![sorted by Abstract field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;IAM;ISE; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ LMV2001 |
Serial |
1581 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Multilocal Creaseness Measure |
Type |
Journal |
|
Year |
2012 |
Publication |
The Insight Journal |
Abbreviated Journal |
IJ |
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Ridges, Valley, Creaseness, Structure Tensor, Skeleton, |
|
|
Abstract ![sorted by Abstract field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission. |
|
|
Address |
|
|
|
Corporate Author |
Alma IT Systems |
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
english |
Summary Language |
english |
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM;ADAS; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VGL2012 |
Serial |
1840 |
|
Permanent link to this record |