Search results for "e learning"
showing 10 items of 2703 documents
Decoding Musical Training from Dynamic Processing of Musical Features in the Brain
2018
AbstractPattern recognition on neural activations from naturalistic music listening has been successful at predicting neural responses of listeners from musical features, and vice versa. Inter-subject differences in the decoding accuracies have arisen partly from musical training that has widely recognized structural and functional effects on the brain. We propose and evaluate a decoding approach aimed at predicting the musicianship class of an individual listener from dynamic neural processing of musical features. Whole brain functional magnetic resonance imaging (fMRI) data was acquired from musicians and nonmusicians during listening of three musical pieces from different genres. Six mus…
Subgrouping factors influencing migraine intensity in women: A semi-automatic methodology based on machine learning and information geometry
2019
[EN] Background Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques. Objective The aim of this study was to analyze critical features that permit the differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks by using machine learning algorithms. Methods Sixty-seven women with migraine participated. Clinical features of migraine, related disability (Migraine Disability Assessment Scale), anxiety/depressive levels (Hospital Anxiety and Depression Scale), anxiety state/trait levels (S…
Emotional and Cognitive Variables Associated with Contamination-Related Obsessive-Compulsive Symptoms
2016
AbstractDifferent variables have been associated with the development/ maintenance of contamination-related obsessive-compulsive disorder (OCD), although the relevance of these factors has not been clearly established. The present study aimed to analyze the relevance and specificity of these variables. Forty-five women with high scores on obsessive-compulsive contamination symptoms (n= 16) or checking symptoms (n= 15), or non-clinical scores (n= 14) participated in a behavioral approach/avoidance task (BAT) with a contamination-OCD stimulus. Vulnerability variables and participants’ emotional, cognitive, physiological and behavioral responses to the BAT were appraised. Results show that fea…
On the complementarity of holistic and analytic approaches to performance assessment scoring.
2019
BACKGROUND A holistic approach to performance assessment recognizes the theoretical complexity of multifaceted critical thinking (CT), a key objective of higher education. However, issues related to reliability, interpretation, and use arise with this approach. AIMS AND METHOD Therefore, we take an analytic approach to scoring students' written responses on a performance assessment. We focus on the complementarity of holistic and analytic approaches and on whether theoretically developed analytical scoring rubrics can produce sub-scores that may measure the 'whole' performance in a holistic assessment. SAMPLE We use data from the Wind Turbines performance assessment, developed in the iPAL p…
Whole-body MRI radiomics model to predict relapsed/refractory Hodgkin Lymphoma: A preliminary study.
2022
Purpose A strong prognostic score that enables a stratification of newly diagnosed Hodgkin Lymphoma (HL) to identify patients at high risk of refractory/relapsed disease is still needed. Our aim was to investigate the potential value of a radiomics analysis pipeline from whole-body MRI (WB-MRI) exams for clinical outcome prediction in patients with Hodgkin Lymphoma (HL). Materials and methods Index lesions from baseline WB-MRIs of 40 patients (22 females; mean age 31.7 ± 11.4 years) with newly diagnosed HL treated by ABVD chemotherapy regimen were manually segmented on T1-weighted, STIR, and DWI images for texture analysis feature extraction. A machine learning approach based on the Extra T…
Differences in the nature of body image disturbances between female obese individuals with versus without a comorbid binge eating disorder: an explor…
2011
Various components of body image were measured to assess body image disturbances in patients with obesity. To overcome limitations of previous studies, a photo distortion technique and a biological motion distortion device were included to assess static and dynamic aspects of body image. Questionnaires assessed cognitive-affective aspects, bodily attitudes, and eating behavior. Patients with obesity and a binge eating disorder (OBE, n = 15) were compared with patients with obesity only (ONB; n = 15), to determine the nature of any differences in body image disturbances. Both groups had high levels of body image disturbances with cognitive-affective deficits. Binge eating disorder (BED) par…
Multimodal Assessment of Long-Term Memory Recall and Reinstatement in a Combined Cue and Context Fear Conditioning and Extinction Paradigm in Humans
2013
Learning to predict danger via associative learning processes is critical for adaptive behaviour. After successful extinction, persisting fear memories often emerge as returning fear. Investigation of return of fear phenomena, e.g. reinstatement, have only recently began and to date, many critical questions with respect to reinstatement in human populations remain unresolved. Few studies have separated experimental phases in time even though increasing evidence shows that allowing for passage of time (and consolidation) between experimental phases has a major impact on the results. In addition, studies have relied on a single psychophysiological dimension only (SCRs/SCL or FPS) which hamper…
How to assess the risks associated with the usage of a medical device based on predictive modeling: the case of an anemia control model certified as …
2021
Background The successful application of Machine Learning (ML) to many clinical problems can lead to its implementation as medical devices (MD), being important to assess the associated risks. Methods An anemia control model (ACM), certified as MD may face adverse events as the result of wrong predictions that are translated into suggestions of doses of erythropoietic stimulating agents to dialysis patients. Risks are assessed as the combination of severity and probability of a given hazard. While severities are typically assessed by clinicians, probabilities are tightly related to the performance of the predictive model. Results A post-marketing dataset formed by all adult patients registe…
Achievement of treatment targets predicts progression of vascular complications in type 1 diabetes.
2021
Abstract Background and aim To study the association between achievement of guideline-defined treatment targets on HbA1c, low-density lipoproteins (LDL-C), and blood pressure with the progression of diabetic complications in patients with type 1 diabetes (T1D). Methods The study included 355 patients at baseline and 114 patients with follow-up data after 3–5 years. Outcome variables were the progression of diabetic kidney disease, retinopathy, or cardiovascular disease (CVD). We used logistic regression and other machine learning algorithms (MLA) to model the association of achievement of treatment targets and probability of progression of complications. Results Achievement of the target bl…
Evaluation of saliva as a complementary technique to the diagnosis of COVID-19:a systematic review
2021
Background Infectious disease coronavirus 2019 (COVID-19) is caused by the SARS-CoV-2 virus, and it mainly affects the upper respiratory tract. The gold standard for its diagnosis is real-time reverse transcription polymerase chain reaction (RT-qPCR) performed on a nasopharyngeal swab. In contrast, testing saliva has significant advantages as a diagnostic method. Material and Methods We searched for articles evaluating saliva as a diagnostic method for COVID-19 on the PUBMED/MEDLINE, WEB OF SCIENCE, COCHRANE, and SCIELO platforms. We initially found 233 articles and 20 were selected for inclusion following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol: 18 c…