Judicialization of the right to health: (Un)compliance of the judicial decisions in Medellin, Colombia
Artículo Materias > Ciencias Sociales Fundación Universitaria Internacional de Colombia > Investigación > Artículos y libros Cerrado Inglés Introduction The judicialization of health arose following the possibility of judicially demanding the right to health before national and international courts. In the case of Colombia, health litigation is done through a constitutional tool called the tutela action, which allows for the immediate protection of fundamental rights. Methods A retrospective cross-sectional study using a probabilistic stratified sample of 1031 users of the tutela actions, in Medellín, Colombia, between 2011 and 2014. Bivariate and multivariate analyses were performed, using statistical tests and multiple logistic regression models. Results According to the respondents, 95.9% of the tutela actions succeeded in favour of the applicant. On average, the judicial process took 10.96 days (SD = 8.09). After the favourable decision of the tutela action, access to health care followed in 76.2% of cases, partial access was found for 14.0% (median, 10 d), and in 9.8% of cases, claimants had not received access to the health care they sought. Conclusion The tutela action is an essential constitutional mechanism that guarantees the access to health services. However, it must be strengthened from the legal point of view through the implementation of monitoring and control actions and by imposing the sanctioning measures and deadlines established in existing legislation. metadata Gómez‐Ceballos, Diego; Craveiro, Isabel y Gonçalves, Luzia mail SIN ESPECIFICAR (2019) Judicialization of the right to health: (Un)compliance of the judicial decisions in Medellin, Colombia. The International Journal of Health Planning and Management, 34 (4). pp. 1277-1289. ISSN 0749-6753
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Introduction The judicialization of health arose following the possibility of judicially demanding the right to health before national and international courts. In the case of Colombia, health litigation is done through a constitutional tool called the tutela action, which allows for the immediate protection of fundamental rights. Methods A retrospective cross-sectional study using a probabilistic stratified sample of 1031 users of the tutela actions, in Medellín, Colombia, between 2011 and 2014. Bivariate and multivariate analyses were performed, using statistical tests and multiple logistic regression models. Results According to the respondents, 95.9% of the tutela actions succeeded in favour of the applicant. On average, the judicial process took 10.96 days (SD = 8.09). After the favourable decision of the tutela action, access to health care followed in 76.2% of cases, partial access was found for 14.0% (median, 10 d), and in 9.8% of cases, claimants had not received access to the health care they sought. Conclusion The tutela action is an essential constitutional mechanism that guarantees the access to health services. However, it must be strengthened from the legal point of view through the implementation of monitoring and control actions and by imposing the sanctioning measures and deadlines established in existing legislation.
| Tipo de Documento: | Artículo |
|---|---|
| Palabras Clave: | Colombia; access to health care; court decisions; judicialization of health; tutela action |
| Clasificación temática: | Materias > Ciencias Sociales |
| Divisiones: | Fundación Universitaria Internacional de Colombia > Investigación > Artículos y libros |
| Depositado: | 14 Mar 2022 23:55 |
| Ultima Modificación: | 14 Mar 2022 23:55 |
| URI: | https://repositorio.unincol.edu.co/id/eprint/556 |
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An Integrated Machine Learning and Genomic Framework for Precise Detection of Gastric Cancer
This study presents a novel integrative approach for the analysis of high-dimensional gene expression data, leveraging the complementary strengths of unsupervised clustering and supervised classification. Using K-means clustering, the dataset is stratified into three distinct clusters, revealing intrinsic biological patterns and relationships. The resulting cluster assignments are subsequently employed as pseudo-labels to train machine learning models, including support vector machines, random forest, and a stacking ensemble classifier. To validate and enhance the robustness of clustering, complementary methodologies such as hierarchical clustering and DBSCAN are employed, with results visualized through PCA-driven dimensionality reduction. The high predictive accuracy achieved by the classifiers underscores the separability and reliability of the identified clusters. Furthermore, feature importance analysis highlighted key genetic determinants within each cluster, offering actionable insights into potential biomarkers and critical genomic features. This framework bridges the gap between exploratory unsupervised learning and predictive supervised modeling, providing a scalable and interpretable methodology for analyzing complex genomic datasets. Its applicability extends to biomarker discovery, patient stratification, and other precision medicine applications, emphasizing its utility in advancing genomic research and clinical practice.
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Iman
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A novel approach for disease and pests detection in potato production system based on deep learning
Vulnerability of potato crops to diseases and pest infestation can affect its quality and lead to significant yield losses. Timely detection of such diseases can help take effective decisions. For this purpose, a deep learning-based object detection framework is designed in this study to identify and classify major potato diseases and pests under real-world field conditions. A total of 2,688 field images were collected from two research farms in Punjab, Pakistan, across multiple growth stages in various seasonal conditions. Excluding 285 symptoms-free images from the earliest collection led to 2,403 images which were annotated into four biotic-stress classes: blight disease (n = 630), leaf spot disease (n = 370), leafroll virus (viral symptom complex; n = 888), and Colorado potato beetle (larvae/adults; n = 515), indicating class imbalance. Several state-of-the-art models were used including YOLOv8 variants (n/s/m), YOLOv7, YOLOv5, and Faster R-CNN, and the results are discussed in relation to recent potato disease classification studies involving cropped leaf images. Stratified splitting (70% training, 20% validation, 10% testing) was applied to preserve class distribution across all subsets. YOLOv8-medium achieve the best performance with mean average precision (mAP)@0.5 of 98% on the held-out test images. Results for stable 5-fold cross-validation show a mean mAP@0.5 of 97.8%, which offers a balance between accuracy and inference time. Model robustness was evaluated using 5-fold cross-validation and repeated training with different random seeds, showing a low variance of ±0.4% mAP. Results demonstrate promising outcomes under the real-world field conditions, while, broader cross-region and cross-season validation is intended for the future.
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Fish consumption and brain structure: a comprehensive systematic review of observational studies
Background Age-related structural changes in the human brain, including cortical atrophy, reductions in grey and white matter volumes, and the accumulation of small vessel–related lesions such as white matter hyperintensities (WMH) and cerebral microbleeds, represent critical biological substrates underlying cognitive decline and dementia. Fish consumption has been associated with slower cognitive decline and reduced risk of dementia, but a comprehensive evaluation of its relation with brain structures is lacking. Aims The aim of this study was to systematically review current scientific literature providing evidence of relation between fish intake and brain structures in human studies. Methods Studies indexed in two major electronic databases have been screened based on a combination of keywords and MeSH terms. Studies were eligible whether they assessed fish consumption in relation to brain structures in the adult populations. Results A total of 24 studies conducted predominantly on older adults met inclusion criteria. Most brain volume measures were obtained via magnetic resonance imaging (MRI) procedures. Higher fish consumption was associated with reduced severity of white matter hyperintensities (a biomarker of cerebral small vessel disease and white matter damage) and cerebral micro-bleed, preservation of certain brain areas volumes (i.e., hippocampus, temporal lobe and periventricle white matter) and cortical thickness of specific areas (i.e., precuneus, parietal, and cingulate grey matter), among others, compared to lower intake. Some analyses found no association and isolated findings suggested possible adverse associations that were not consistently replicated. Studies reporting null findings may underline the possible relevance of the overall diet (i.e., adherence to the Mediterranean diet). Conclusions Inclusion of fish in a healthy and balanced diet is associated with better white matter grades on MRI and slower progression of white matter hyperintensities and reduction of vascular-related lesions of the aging brain, suggesting a potential role in preventing neurocognitive deterioration. Heterogeneity across studies underscores the need for additional studies.
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Background: Mild Cognitive Impairment (MCI) is viewed as a transitional stage between normal brain aging and dementia and is characterized by subtle cognitive deficits without significant impairment in daily functioning. Growing evidence supports the contribution of neuroinflammation and modifiable lifestyle factors, including diet, in the progression of cognitive decline.Aim: This study aimed to investigate the association between adherence to the Mediterranean diet, neuroinflammatory biomarkers, and MCI status in older adults.Design: Ninety-two participants were enrolled in this cross-sectional study, including 37 subjects with MCI. Dietary intake was assessed using a validated food frequency questionnaire (FFQ) and adherence to the Mediterranean diet explored through the MedDietScore. Plasma levels of TGF-β1 and TNF-α were measured by ELISA. Cognitive status was evaluated using the Mini Mental Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), both adjusted for age and education. Statistical analyses included non-parametric tests, correlation analysis, and logistic regression models.Results: MCI patients showed significantly reduced plasma levels of TGF-β1 and increased TNF-α concentrations compared to other participants. After adjustment for potential confounding factors, greater adherence to the Mediterranean diet was associated with a lower likelihood of MCI in a dose–response manner (highest versus lowest adherence quartile, odds ratio: 0.07, 95% confidence interval: 0.01–0.60). Additional adjustment for inflammatory biomarkers attenuated the associations, suggesting a potential mediating role.Conclusion: Our findings showed that higher adherence to Mediterranean diet is associated with lower likelihood of being MCI. Such a relation might be, at least in part, mediated by inflammatory biomarkers. Overall, these results support the role of dietary modulation in preventive strategies against cognitive decline and progression into MCI.
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Correction: Enhancing fault detection in new energy vehicles via novel ensemble approach
In the original version of this Article, Umair Shahid was incorrectly listed as a corresponding author. The correct corresponding authors for this Article are Imran Ashraf and Kashif Munir. Correspondence and request for materials should be addressed to ashrafimran@live.com and kashif.munir@kfueit.edu.pk.
Iqra Akhtar mail , Mahnoor Nabeel mail , Umair Shahid mail , Kashif Munir mail , Ali Raza mail , Irene Delgado Noya mail irene.delgado@uneatlantico.es, Santos Gracia Villar mail santos.gracia@uneatlantico.es, Imran Ashraf mail ,
Akhtar