Context encoder transfer learning approaches for retinal image analysis

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG.[Abstract]: During the last years, deep learning techniques have emerged as powerful alternatives to solve biomedical image analysis problems. However, the training of deep neural networks usually needs great amounts of labeled data to be done effectively. This is even more critical in the case of biomedical imaging due to the added difficulty of obtaining data labeled by experienced clinicians. To mitigate the impact of data scarcity, one of the most commonly used strategies is transfer learning. Nevertheless, the success of this approach depends on the effectiveness of the available pre-training techniques for learning from little or no labeled data. In this work, we explore the application of the Context Encoder paradigm for transfer learning in the domain of retinal image analysis. To this aim, we propose several approaches that allow to work with full resolution images and improve the recognition of the retinal structures. In order to validate the proposals, the Context Encoder pre-trained models are fine-tuned to perform two relevant tasks in the domain: vessels segmentation and fovea localization. The experiments performed on different public datasets demonstrate that the proposed Context Encoder approaches allow mitigating the impact of data scarcity, being superior to previous alternatives in this domain.Xunta de Galicia; ED481A 2021/196Xunta de Galicia; ED481B-2022-025Xunta de Galicia; ED431C 2020/24Xunta de Galicia; IN845D 2020/38Xunta de Galicia; ED431G 2019/01This research was funded by Instituto de Salud Carlos III, Gov- ernment of Spain, DTS18/00136 research project; Ministerio de Cien- cia e Innovación y Universidades, Government of Spain, RTI2018- 095894-B-I00 research project; Ministerio de Ciencia e Innovación, Government of Spain through the research project with reference PID2019-108435RB-I00; Consellería de Cultura, Educación e Univer- sidade, Xunta de Galicia, Spain through the predoctoral grant contract ref. ED481A 2021/196 and postdoctoral grant contract ref. ED481B- 2022-025; and Grupos de Referencia Competitiva, grant ref. ED431C 2020/24; Axencia Galega de Innovación (GAIN), Spain, Xunta de Galicia, grant ref. IN845D 2020/38; CITIC, Centro de Investigación de Galicia, Spain ref. ED431G 2019/01, receives financial support from Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia, Spain, through the ERDF (80%) and Secretaría Xeral de Universidades (20%). Funding for open access charge: Universidade da Coruña/CISUG

Interference between cues in human contingency learning: A review, new data and a potential general explanation based on propositional models

Interference between cues (IbC) is a phenomenon in which associat- ing a cue with an outcome interferes retroactively with the retrieval of previously acquired association between another cue and the same outcome. In this presentation, we review those situations in which IbC has been found and not found in the literature, and propose a general mechanism responsible of IbC based on propositional mod- els. IbC would take place in those situations in which participants had reasonable expectations of univoque relations between cues and outcomes/responses but later these expectations are not fulfilled. We present three experiments that tested this hypothesis. In the first one, the likelihood of univoque relations was manipulated by using a dif- ferent number of available responses, while in the second partici- pants were pretrained with univoque or non univoque filler relations. In both cases reducing the likelihood of the expectation of univoque relations reduced the magnitude of IbC, supporting the proposed hy- pothesis. Finally, in the third experiment we showed that when the interfering association is presented using instructions it also produces IbC, as in a trial-by-trial learning. Its magnitude was similar or high- er, depending on the type of measurement used. These results suggest that a high-level propositional inference produces IbC.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models

Funding for open access charge: Universidade da Coruña/CISUG.[Abstract]: COVID-19 is a global threat for the healthcare systems due to the rapid spread of the pathogen that causes it. In such situation, the clinicians must take important decisions, in an environment where medical resources can be insufficient. In this task, the computer-aided diagnosis systems can be very useful not only in the task of supporting the clinical decisions but also to perform relevant analyses, allowing them to understand better the disease and the factors that can identify the high risk patients. For those purposes, in this work, we use several machine learning algorithms to estimate the outcome of COVID-19 patients given their clinical information. Particularly, we perform 2 different studies: the first one estimates whether the patient is at low or at high risk of death whereas the second estimates if the patient needs hospitalization or not. The results of the analyses of this work show the most relevant features for each studied scenario, as well as the classification performance of the considered machine learning models. In particular, the XGBoost algorithm is able to estimate the need for hospitalization of a patient with an AUC-ROC of 0.8415± 0.0217 while it can also estimate the risk of death with an AUC-ROC of 0.7992±0.0104. Results have demonstrated the great potential of the proposal to determine those patients that need a greater amount of medical resources for being at a higher risk. This provides the healthcare services with a tool to better manage their resources.Xunta de Galicia; ED481A 2021/196Xunta de Galicia; ED431C 2020/24Xunta de Galicia; IN845D 2020/38Xunta de Galicia; ED431G 2019/01This research was funded by ISCIII, Government of Spain, DTS18/00136 research project; Ministerio de Ciencia e Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project; Ministerio de Ciencia e Innovación, Government of Spain through the research project with reference PID2019-108435RB-I00; CCEU, Xunta de Galicia through the predoctoral grant contract ref. ED481A 2021/196; and Grupos de Referencia Competitiva, grant ref. ED431C 2020/24; Axencia Galega de Innovación (GAIN), Xunta de Galicia, grant ref. IN845D 2020/38; CITIC, Centro de Investigación de Galicia ref. ED431G 2019/01, receives financial support from CCEU, Xunta de Galicia , through the ERDF (80%) and Secretaría Xeral de Universidades (20%). Funding for open access charge: Universidade da Coruña/CISUG

Perceptions of Heritage among Students of Early Childhood and Primary Education

In recent decades, a growing awareness of the importance of preserving cultural heritage as a means of promoting sustainable development has been accompanied by a similar re-evaluation of the role of heritage education as a key driver of citizen engagement. The development and implementation of heritage education at all levels, particularly in the context of teacher training, is of vital importance. The aim of this study is to analyse student teachers’ understanding of heritage and its potential as an educational tool, in order to identify measures to enhance teacher training and practice with respect to heritage and heritage education. The research design consists of a comparative study of a non-random sample of 149 trainee teachers undertaking Bachelor’s degrees in Early Childhood Education and Primary Education at the University of Córdoba (Spain). The results reveal a mainly cultural conception of heritage among both groups, based on local material elements, and little sense of the link between heritage and present-day life. The students studying early childhood education were found to display a more specific knowledge of heritage in their answers, while the primary education students showed a greater awareness of identity and values as features of cultural heritage

Neural signatures of predictive language processing in Parkinson's disease with and without mild cognitive impairment

Altres ajuts: Fundació la Marató de TV3 (2014/U/477, 20142910)Cognitive deficits are common in Parkinson's disease (PD), with some PD patients meeting criteria for mild cognitive impairment (MCI). An unaddressed question is whether linguistic prediction is preserved in PD. This ability is nowadays deemed crucial for achieving fast and efficient comprehension, and it may be negatively impacted by cognitive deterioration in PD. To fill this gap of knowledge, we used event-related potentials (ERPs) to evaluate mechanisms of linguistic prediction in a sample of PD patients (on dopamine compensation) with and without MCI. To this end, participants read sentence contexts that were predictive or not about a sentence-final word. The final word appeared after one sec, matching or mismatching the prediction. The introduction of the interval allowed to capture neural responses both before and after sentence-final words, reflecting semantic anticipation and semantic processing. PD patients with normal cognition (N = 58) showed ERP responses comparable to those of matched controls. Specifically, in predictive contexts, a slow negative potential developed prior to sentence-final words, reflecting semantic anticipation. Later, expected words elicited reduced N400 responses (compared to unexpected words), indicating facilitated semantic processing. PD patients with MCI (N = 20) showed, in addition, a prolongation of the N400 congruency effect (compared to matched PD patients without MCI), indicating that further cognitive decline impacts semantic processing. Finally, lower verbal fluency scores correlated with prolonged N400 congruency effects and with reduced pre-word differences in all PD patients (N = 78). This relevantly points to a role of deficits in temporal-dependent mechanisms in PD, besides prototypical frontal dysfunction, in altered semantic anticipation and semantic processing during sentence comprehension

A randomized comparison ofrepeat stenting with balloon angioplasty in patients with in-stent restenosis

AbstractObjectivesThis randomized trial compared repeat stenting with balloon angioplasty (BA) in patients with in-stent restenosis (ISR).BackgroundStent restenosis constitutes a therapeutic challenge. Repeat coronary interventions are currently used in this setting, but the recurrence risk remains high.MethodsWe randomly assigned 450 patients with ISR to elective stent implantation (224 patients) or conventional BA (226 patients). Primary end point was recurrent restenosis rate at six months. Secondary end points included minimal lumen diameter (MLD), prespecified subgroup analyses, and a composite of major adverse events.ResultsProcedural success was similar in both groups, but in-hospital complications were more frequent in the balloon group. After the procedure MLD was larger in the stent group (2.77 ± 0.4 vs. 2.25 ± 0.5 mm, p < 0.001). At follow-up, MLD was larger after stenting when the in-lesion site was considered (1.69 ± 0.8 vs. 1.54 ± 0.7 mm, p = 0.046). However, the binary restenosis rate (38% stent group, 39% balloon group) was similar with the two strategies. One-year event-free survival (follow-up 100%) was also similar in both groups (77% stent vs. 71% balloon, p = 0.19). Nevertheless, in the prespecified subgroup of patients with large vessels (≥3 mm) the restenosis rate (27% vs. 49%, p = 0.007) and the event-free survival (84% vs. 62%, p = 0.002) were better after repeat stenting.ConclusionsIn patients with ISR, repeat coronary stenting provided better initial angiographic results but failed to improve restenosis rate and clinical outcome when compared with BA. However, in patients with large vessels coronary stenting improved the long-term clinical and angiographic outcome

Autoantibody screening in Guillain-Barré syndrome

Background: Guillain-Barré syndrome (GBS) is an acute inflammatory neuropathy with a heterogeneous presentation. Although some evidences support the role of autoantibodies in its pathogenesis, the target antigens remain unknown in a substantial proportion of GBS patients. The objective of this study is to screen for autoantibodies targeting peripheral nerve components in Guillain-Barré syndrome. Methods: Autoantibody screening was performed in serum samples from all GBS patients included in the International GBS Outcome study by 11 different Spanish centres. The screening included testing for anti-ganglioside antibodies, anti-nodo/paranodal antibodies, immunocytochemistry on neuroblastoma-derived human motor neurons and murine dorsal root ganglia (DRG) neurons, and immunohistochemistry on monkey peripheral nerve sections. We analysed the staining patterns of patients and controls. The prognostic value of anti-ganglioside antibodies was also analysed. Results: None of the GBS patients (n = 100) reacted against the nodo/paranodal proteins tested, and 61 (61%) were positive for, at least, one anti-ganglioside antibody. GBS sera reacted strongly against DRG neurons more frequently than controls both with IgG (6% vs 0%; p = 0.03) and IgM (11% vs 2.2%; p = 0.02) immunodetection. No differences were observed in the proportion of patients reacting against neuroblastoma-derived human motor neurons. Reactivity against monkey nerve tissue was frequently detected both in patients and controls, but specific patterns were only detected in GBS patients: IgG from 13 (13%) patients reacted strongly against Schwann cells. Finally, we confirmed that IgG anti-GM1 antibodies are associated with poorer outcomes independently of other known prognostic factors. Conclusion: Our study confirms that (1) GBS patients display a heterogeneous repertoire of autoantibodies targeting nerve cells and structures; (2) gangliosides are the most frequent antigens in GBS patients and have a prognostic value; (3) further antigen-discovery experiments may elucidate other potential antigens in GBS