Plan de intervención de Fisioterapia en la Incontinencia Urinaria Mixta: a propósito de un caso

Resumen: Introducción. La incontinencia urinaria mixta (IUM) es el segundo tipo de incontinencia urinaria más frecuente en mujeres y provoca un alto impacto en la calidad de vida. Se asocia con factores que debilitan el suelo pélvico como la edad, la menopausia y los antecedentes obstétrico-ginecológicos. Mediante la aplicación de diferentes técnicas fisioterapéuticas se puede mejorar la contracción y la condición muscular del suelo pélvico. Objetivos. Descripción de un caso clínico de una paciente con incontinencia urinaria mixta, presentando los resultados obtenidos tras la aplicación de un plan de tratamiento fisioterápico para restablecer la continencia y mejorar la calidad de vida y la autoestima de la paciente. Metodología. Se describe un estudio intrasujeto N=1 de tipo AB en el que para conocer la evolución de la paciente, se realizaron dos valoraciones completas pre y post-tratamiento. El tratamiento aplicado consistió en 20 sesiones, combinando sesiones individuales de electromiografía-biofeedback y electroestimulación y sesiones grupales para el aprendizaje de ejercicios para la musculatura del suelo pélvico. Además, se enseñaron medidas higiénico-dietéticas para el cuidado del suelo pélvico. Desarrollo. Al finalizar el tratamiento, se observó una mejora de las condiciones musculares del suelo pélvico y del compartimento abdominal, además de una disminución de la frecuencia de micciones. Sin embargo, no se obtuvo la mejora esperable en la calidad de vida y la autoestima de la paciente. Conclusiones. El plan de intervención en fisioterapia ha resultado efectivo, en relación a los objetivos propuestos en este caso, a excepción de la calidad de vida, que aún continúa afectada por la persistencia de los síntomas de IUU. Palabras clave: suelo pélvico, incontinencia urinaria, fisioterapia, EMSP, GAH

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Abstract Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists’ decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists’ diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists’ confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists’ willingness to adopt such XAI systems, promoting future use in the clinic

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists’ decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists’ diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists’ confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists’ willingness to adopt such XAI systems, promoting future use in the clinic. © 2024, The Author(s).53 − 5400.1-007/

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora