Revisiting Hidden Representations in Transfer Learning for Medical Imaging

While a key component to the success of deep learning is the availability of massive amounts of training data, medical image datasets are often limited in diversity and size. Transfer learning has the potential to bridge the gap between related yet different domains. For medical applications, however, it remains unclear whether it is more beneficial to pre-train on natural or medical images. We aim to shed light on this problem by comparing initialization on ImageNet and RadImageNet on seven medical classification tasks. We investigate their learned representations with Canonical Correlation Analysis (CCA) and compare the predictions of the different models. We find that overall the models pre-trained on ImageNet outperform those trained on RadImageNet. Our results show that, contrary to intuition, ImageNet and RadImageNet converge to distinct intermediate representations, and that these representations are even more dissimilar after fine-tuning. Despite these distinct representations, the predictions of the models remain similar. Our findings challenge the notion that transfer learning is effective due to the reuse of general features in the early layers of a convolutional neural network and show that weight similarity before and after fine-tuning is negatively related to performance gains.Comment: Submitted to the CHIL 2023 Track 2: Applications and Practic

Detecting Shortcuts in Medical Images -- A Case Study in Chest X-rays

The availability of large public datasets and the increased amount of computing power have shifted the interest of the medical community to high-performance algorithms. However, little attention is paid to the quality of the data and their annotations. High performance on benchmark datasets may be reported without considering possible shortcuts or artifacts in the data, besides, models are not tested on subpopulation groups. With this work, we aim to raise awareness about shortcuts problems. We validate previous findings, and present a case study on chest X-rays using two publicly available datasets. We share annotations for a subset of pneumothorax images with drains. We conclude with general recommendations for medical image classification.Comment: Submitted to ISBI 202

Precise Proximal Femur Fracture Classification for Interactive Training and Surgical Planning

We demonstrate the feasibility of a fully automatic computer-aided diagnosis (CAD) tool, based on deep learning, that localizes and classifies proximal femur fractures on X-ray images according to the AO classification. The proposed framework aims to improve patient treatment planning and provide support for the training of trauma surgeon residents. A database of 1347 clinical radiographic studies was collected. Radiologists and trauma surgeons annotated all fractures with bounding boxes, and provided a classification according to the AO standard. The proposed CAD tool for the classification of radiographs into types "A", "B" and "not-fractured", reaches a F1-score of 87% and AUC of 0.95, when classifying fractures versus not-fractured cases it improves up to 94% and 0.98. Prior localization of the fracture results in an improvement with respect to full image classification. 100% of the predicted centers of the region of interest are contained in the manually provided bounding boxes. The system retrieves on average 9 relevant images (from the same class) out of 10 cases. Our CAD scheme localizes, detects and further classifies proximal femur fractures achieving results comparable to expert-level and state-of-the-art performance. Our auxiliary localization model was highly accurate predicting the region of interest in the radiograph. We further investigated several strategies of verification for its adoption into the daily clinical routine. A sensitivity analysis of the size of the ROI and image retrieval as a clinical use case were presented.Comment: Accepted at IPCAI 2020 and IJCAR

El clima laboral y la satisfacción de los colaboradores de la Superintendencia Nacional de los Registros Públicos (Sunarp) – Zona Registral N° V Sede Trujillo, año 2018

La presente investigación tuvo como objetivo principal, establecer la relación que existe entre el clima laboral y la satisfacción de los colaboradores de la Superintendencia Nacional de los Registros Públicos (SUNARP) de la Zona Registral N° V – Sede Trujillo, en el año 2018. Para lograr el propósito de la misma se procedió a determinar el nivel de satisfacción de los colaboradores y la dimensión del clima laboral que más repercute en ello. Se estudiaron diversas teorías de autores para identificar cual se asemeja a la Entidad Pública en estudio. Se trabajó con una muestra aleatoria de 161 colaboradores pertenecientes a todas las unidades, y con el diseño descriptivo correlacional. Se elaboró un cuestionario para recopilar la información requerida, los datos fueron organizados en una matriz de resultados por variables e indicadores en hojas de cálculo Excel. Como resultado se observa que los valores del coeficiente de correlación de Spearman, se encuentra entre 0,00 y 0,04 (existiendo una relación directa) con niveles de significancia p = 0,000 menores al 5% (p < 0.05), la cual quiere decir que los indicadores del clima laboral se relacionan significativamente con los indicadores de la satisfacción de los colaboradores de la Superintendencia Nacional de los Registros Públicos.The main objective of this research was to establish the relationship between the work environment and the satisfaction of the employees of the National Superintendence of Public Registries (SUNARP) of the Registration Zone No. V - Trujillo Office, in 2018. To achieve the purpose of the same was determined to the level of satisfaction of employees and the dimension of the work environment that most affects it. Various theories of authors were studied to identify which resembles the Public Entity under study. We worked with a random sample of 161 collaborators belonging to all the units, and with the descriptive correlational design. A questionnaire was developed to gather the required information, the data were organized in a matrix of results by variables and indicators in Excel spreadsheets. As a result, it is observed that the values of the Spearman correlation coefficient are between 0,00 and 0,04 (there being a direct relationship) with levels of significance p = 0.000 lower than 5% (p <0.05), which means that the indicators of the work climate are significantly related to the indicators of the satisfaction of the employees of the National Superintendence of the Public Records.Tesi

Uso de catecolamina para la diferenciación de células madre a cardiomiocitos.

Uso de catecolamina para la diferenciación de células madre a cardiomiocitos. La presente invención se refiere al uso de catecolamina para la diferenciación de células madre a cardiomiocitos y su maduración así como un método para la obtención y maduración de estas células cardíacas. Además, la catecolamina puede usarse para la preparación de un medicamento destinado al tratamiento de un daño cardíaco.Peer reviewedConsejo Superior de Investigaciones Científicas (España), Universidad de Extremadura, Universidad de JaénB1 Patente sin examen previ

Augmenting Chest X-ray Datasets with Non-Expert Annotations

The advancement of machine learning algorithms in medical image analysis requires the expansion of training datasets. A popular and cost-effective approach is automated annotation extraction from free-text medical reports, primarily due to the high costs associated with expert clinicians annotating chest X-ray images. However, it has been shown that the resulting datasets are susceptible to biases and shortcuts. Another strategy to increase the size of a dataset is crowdsourcing, a widely adopted practice in general computer vision with some success in medical image analysis. In a similar vein to crowdsourcing, we enhance two publicly available chest X-ray datasets by incorporating non-expert annotations. However, instead of using diagnostic labels, we annotate shortcuts in the form of tubes. We collect 3.5k chest drain annotations for CXR14, and 1k annotations for 4 different tube types in PadChest. We train a chest drain detector with the non-expert annotations that generalizes well to expert labels. Moreover, we compare our annotations to those provided by experts and show "moderate" to "almost perfect" agreement. Finally, we present a pathology agreement study to raise awareness about ground truth annotations. We make our annotations and code available

Análisis de la guarda y custodia a raíz de la Ley 5/2005

En España la Ley de Divorcio entró en vigor hace treinta años y durante este tiempo se han producido cambios en la dinámica familiar que han obligado a modificar los sistemas de relación parentofilial. Hasta hace relativamente poco tiempo era infrecuente la atribución de la guarda y custodia compartida, poco demandada por los padres, siendo más común atribuir la guarda y custodia monoparental. Con la Ley 15/05 de 8 de Julio de 2005, por la que se modifica el Código Civil y la Ley de Enjuiciamiento Civil en materia de separación y divorcio, se ofrece la posibilidad de regular la custodia compartida. Como miembros de los Equipos Técnicos Judiciales y agentes directos en la valoración de esta materia, en el presente trabajo plasmaremos los resultados de la investigación realizada durante los años 2008, 2009 y 2010 de todos los casos solicitados por parte del juez a fin de valorar una custodia compartida cuando una de las partes así lo solicita

Medical-based Deep Curriculum Learning for Improved Fracture Classification

International audienceAbstract. Current deep-learning-based methods do not easily integrate into clinical protocols, neither take full advantage of medical knowledge.In this work, we propose and compare several strategies relying on curriculum learning, to support the classification of proximal femur fracturefrom X-ray images, a challenging problem as reflected by existing intra- and inter-expert disagreement. Our strategies are derived from knowledgesuch as medical decision trees and inconsistencies in the annotations of multiple experts, which allows us to assign a degree of diculty to eachtraining sample. We demonstrate that if we start learning \easy" examples and move towards \hard", the model can reach better performance,even with fewer data. The evaluation is performed on the classification of a clinical dataset of about 1000 X-ray images. Our results show that,compared to class-uniform and random strategies, the proposed medical knowledge-based curriculum, performs up to 15% better in terms ofaccuracy, achieving the performance of experienced trauma surgeons. Keywords: Curriculum learning, multi-label classification, bone fractures, computer-aided diagnosis, medical decision tre

Propuesta estratégica de mejora en la implementación de los estándares mínimos del Sistema de Gestión de la Seguridad y Salud en el Trabajo (SG-SST) en la Empresa Promociones y Cobranzas Beta para 2020.

Promociones y Cobranzas Beta S.A. es una empresa que se dedica a diseñar y desarrollar estrategias para la gestión de cobro a los clientes del banco Davivienda, encaminados a brindar servicios de calidad y excelencia siempre pensando en el bienestar de sus clientes tanto internos como externos. Es por esto, que a través de este trabajo buscamos realizar una evaluación inicial del sistema de gestión seguridad y salud en el trabajo SG-SST de la empresa dando cumplimiento a la normatividad vigente de acuerdo al decreto 1072 de 2015 con el fin de identificar el nivel de cumplimiento de la organización y evaluar las falencias del sistema de gestión que permita proponer un plan de mejoramiento que se puede implementar en la compañía asegurando la normatividad vigente y que permita mejorar el bienestar de los trabajadores mitigando los riesgos, incidentes o accidentes de trabajo para que los empleados se sientan seguros tanto física, como mental y socialmente.Promociones y Cobranzas Beta S.A. is a company dedicate to design and develop collection management strategies for costumers of Davivienda, aimed to bring services of quality and excelence, Always thinking un well-being of internal and external costumers. That is why, through this work, we seek to carry out an initial evaluation of the company's occupational safety and health management system SG-SST, complying with current regulations in accordance with Decree 1072 of 2015 in order to identify the level of compliance of the organization and assess the failings of the management system that allows proposing an improvement plan that can be implemented in the company ensuring current regulations and that allows improving the well-being of workers mitigating risks, incidents or accidents at work so that employees feel physically, mentally and socially safe.Promociones y Cobranzas Beta SA is a company that is dedicated to designing and developing collection management strategies for clients of the Davivienda bank, aimed at providing quality and excellence services always thinking about the well-being of its internal and external clients. That is why, through this work, we seek to carry out an initial evaluation of the company's occupational safety and health management system SG-SST, complying with current regulations in accordance with Decree 1072 of 2015 in order to identify the level of compliance of the organization and assess the failings of the management system that allows proposing an improvement plan that can be implemented in the company ensuring current regulations and that allows improving the well-being of workers mitigating risks, incidents or accidents at work so that employees feel secure physically, mentally and socially