Towards a More Rigorous Science of Blindspot Discovery in Image Models

A growing body of work studies Blindspot Discovery Methods ("BDM"s): methods that use an image embedding to find semantically meaningful (i.e., united by a human-understandable concept) subsets of the data where an image classifier performs significantly worse. Motivated by observed gaps in prior work, we introduce a new framework for evaluating BDMs, SpotCheck, that uses synthetic image datasets to train models with known blindspots and a new BDM, PlaneSpot, that uses a 2D image representation. We use SpotCheck to run controlled experiments that identify factors that influence BDM performance (e.g., the number of blindspots in a model, or features used to define the blindspot) and show that PlaneSpot is competitive with and in many cases outperforms existing BDMs. Importantly, we validate these findings by designing additional experiments that use real image data from MS-COCO, a large image benchmark dataset. Our findings suggest several promising directions for future work on BDM design and evaluation. Overall, we hope that the methodology and analyses presented in this work will help facilitate a more rigorous science of blindspot discovery

Cuando los instagrammers son los adultos

En el marco de los temas relacionados al marketing, se encuentran varias estrategias que afectan la conducta de compra de los consumidores con la finalidad de informar o persuadir sobre los beneficios que brinda determinado producto o servicio. Las empresas ecuatorianas utilizan dichas estrategias para captar la atención de clientes actuales y potenciales, con la finalidad de generar: posicionamiento de mercado, top of mind, captación e incremento del market share, satisfacción de los clientes y por supuesto, mayores ventas de los bienes que ofrecen. Esta recopilación de artículos académicos, aborda diversas estrategias manejadas por las pymes ecuatorianas, con sus correspondientes respuestas de mercado en los consumidores, manejando temas tales como: neuromarketing, marketing digital, cultura de consumo y comportamiento de compra

Priorities in Cardio-Oncology Basic and Translational Science

Despite improvements in cancer survival, cancer therapy–related cardiovascular toxicity has risen to become a prominent clinical challenge. This has led to the growth of the burgeoning field of cardio-oncology, which aims to advance the cardiovascular health of cancer patients and survivors, through actionable and translatable science. In these Global Cardio-Oncology Symposium 2023 scientific symposium proceedings, we present a focused review on the mechanisms that contribute to common cardiovascular toxicities discussed at this meeting, the ongoing international collaborative efforts to improve patient outcomes, and the bidirectional challenges of translating basic research to clinical care. We acknowledge that there are many additional therapies that are of significance but were not topics of discussion at this symposium. We hope that through this symposium-based review we can highlight the knowledge gaps and clinical priorities to inform the design of future studies that aim to prevent and mitigate cardiovascular disease in cancer patients and survivors.</p

Creació de recursos en línea per a l’autoaprenentage, foment de l’esperit crític i emprenedor i formació d’un comité d’avaluació externa en el màster MERIT

El projecte es desenvolupa en el marc de la titulació oficial de màster MERIT del Departament de Teoria del Senyal i Comunicacions. El màster, orientat a la recerca i integrat dins del programa Erasmus Mundus, presenta trets esfecífics donat l’origen variat dels estudiants i que s’imparteix integrament en anglès. El projecte s’articula en 4 eixos: 1. Millorar el sistema d’acollida i integració dels estudiants en el programa formatiu del màster mitjançant la creació de recursos docents en xarxa (campus digital), i la incorporació de nous elements tecnològics a l’aula. 2. Millorar el seguiment dels estudiants de primer curs mitjançant suport als professors per part d’estudiants avantatjats de segon curs. 3. Fomentar el desenvolupament de competències transversals dels estudiants mitjançant la impartició d’assignatures que fomentin l’esperit crític i emprenedor. 4. Establir un mecanisme d’assegurament de la qualitat basat en un Comitè d’Avaluació Extern (CAE) d’acord amb les directrius de l’AQUPeer Reviewe

Colombian consensus recommendations for diagnosis, management and treatment of the infection by SARS-COV-2/ COVID-19 in health care facilities - Recommendations from expert´s group based and informed on evidence

La Asociación Colombiana de Infectología (ACIN) y el Instituto de Evaluación de Nuevas Tecnologías de la Salud (IETS) conformó un grupo de trabajo para desarrollar recomendaciones informadas y basadas en evidencia, por consenso de expertos para la atención, diagnóstico y manejo de casos de Covid 19. Estas guías son dirigidas al personal de salud y buscar dar recomendaciones en los ámbitos de la atención en salud de los casos de Covid-19, en el contexto nacional de Colombia

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Where Does My Model Underperform? A Human Evaluation of Slice Discovery Algorithms

Machine learning (ML) models that achieve high average accuracy can still underperform on semantically coherent subsets ("slices") of data. This behavior can have significant societal consequences for the safety or bias of the model in deployment, but identifying these underperforming slices can be difficult in practice, especially in domains where practitioners lack access to group annotations to define coherent subsets of their data. Motivated by these challenges, ML researchers have developed new slice discovery algorithms that aim to group together coherent and high-error subsets of data. However, there has been little evaluation focused on whether these tools help humans form correct hypotheses about where (for which groups) their model underperforms. We conduct a controlled user study (N = 15) where we show 40 slices output by two state-of-the-art slice discovery algorithms to users, and ask them to form hypotheses about an object detection model. Our results provide positive evidence that these tools provide some benefit over a naive baseline, and also shed light on challenges faced by users during the hypothesis formation step. We conclude by discussing design opportunities for ML and HCI researchers. Our findings point to the importance of centering users when creating and evaluating new tools for slice discovery

Un mapa de riesgo de crédito para el sistema financiero colombiano

El mapa de riesgo es una herramienta usual en la literatura de riesgo operacional que ha sido empleada recientemente en el análisis del riesgo de crédito en el sector financiero. En línea con estos desarrollos, el presente documento propone un mapa en el que se cuantifica la probabilidad de deterioro y el daño potencial asociado a la ocurrencia de choques macroeconómicos adversos sobre la probabilidad de incumplimiento de los principales sectores económicos (hogares y empresas). La metodología utiliza como medida de daño potencial la distancia horizontal entre la distribución de pérdidas que se construye a partir delos pronósticos de las variables macroeconómicas en un escenario base, y la distribución bajo un escenario macroeconómico adverso; estas distribuciones son obtenidas a través de un modelo de regresión por cuantiles. Finalmente se obtiene una representación gráfica que permite hacer un seguimiento de la vulnerabilidad del sistema financiero ante distintos choques. Los resultados indican que un incremento de la tasa de interés generaría el mayor deterioro del indicador de mora, aunque la probabilidad de un aumento drástico es baja. A su vez, un crecimiento significativo del desempleo en el caso de los hogares o una reducción de los ingresos por ventas en el caso de las empresas, son los eventos con mayor probabilidad de ocurrencia.A risk map is often employed as a tool in operational risk management and has been used recently to monitor and analyze credit risk in financial systems. In line with current literature on the subject, this document proposes a risk map that quantifies the default probability and the potential damage associated with adverse macroeconomic shocks on important economic sectors as households and enterprises. We use quantile regression to estimate forecast distributions conditional to stress scenarios in order to quantify the potential damage of such adverse macroeconomic shocks. The results are summarized in a graphic representation which allows us to identify the financial system vulnerabilities. The map indicates that an adverse shock over the interest rate would generate the major increase of the risk indicator. At the same time, an increase in unemployment and a reduction in sales income are the most probable events

"Sport, Social Inclusion, and Community Experiences in Latin America"

Trece autores latinoamericanos se reunieron para crear Deporte, inclusión social y experiencias comunitarias en América Latina, una obra que compila el trabajo de docentes e investigadores que desde sus territorios han descubierto cómo a través del deporte se puede aportar al cambio de una sociedad. Cada capítulo abarca distintas experiencias donde los actores más destacados son el Estado, como figura garante de los derechos; el docente de Educación Física, como ejecutor de las políticas y responsable de prácticas que contribuyan al desarrollo de una comunidad; y la actividad física, como instrumento para generar diversas iniciativas de inclusión. El libro ofrece un panorama sobre las distintas realidades de países como Colombia, México, Argentina y Cuba, discutidas en la tercera Jornada Latinoamericana y Caribeña de Deporte Social y Recreación para la Inclusión, con el objetivo de mantener una reflexión permanente y una apertura al diálogo académico sobre el deporte