Inteligencia artificial en enfermedades infecciosas / Artificial intelligence in infectious diseases

Estamos asistiendo a una verdadera revolución tecnológi-ca en el campo de la salud. Los procesos basados en la aplicación de la inteligencia artificial (IA) y el aprendizaje automático (AA) están llegando progresivamente a todas las áreas disciplinares, y su aplicación en el campo de las enfermedades infecciosas es ya vertiginoso, acelerado por la pandemia de COVID-19.Hoy disponemos de herramientas que no solamente pue-den asistir o llevar adelante el proceso de toma de deci-siones basadas en guías o algoritmos, sino que también pueden modificar su desempeño a partir de los procesos previamente realizados. Desde la optimización en la identificación de microorganis-mos resistentes, la selección de candidatos a participar en ensayos clínicos, la búsqueda de nuevos agentes terapéu-ticos antimicrobianos, el desarrollo de nuevas vacunas, la predicción de futuras epidemias y pandemias, y el segui-miento clínico de pacientes con enfermedades infecciosas hasta la asignación de recursos en el curso de manejo de un brote son actividades que hoy ya pueden valerse de la inteligencia artificial para obtener un mejor resultado. El desarrollo de la IA tiene un potencial de aplicación expo-nencial y sin dudas será uno de los determinantes principa-les que moldearán la actividad médica del futuro cercano.Sin embargo, la maduración de esta tecnología, necesaria para su inserción definitiva en las actividades cotidianas del cuidado de la salud, requiere la definición de paráme-tros de referencia, sistemas de validación y lineamientos regulatorios que todavía no existen o son aún solo inci-pientes

We are in the midst of a true technological revolution in healthcare. Processes based upon artificial intelligence and machine learning are progressively touching all disciplinary areas, and its implementation in the field of infectious diseases is astonishing, accelerated by the COVID-19 pandemic. Today we have tools that can not only assist or carry on decision-making processes based upon guidelines or algorithms, but also modify its performance from the previously completed tasks. From optimization of the identification of resistant pathogens, selection of candidates for participating in clinical trials, the search of new antimicrobial therapeutic agents, the development of new vaccines, the prediction of future epidemics and pandemics, the clinical follow up of patients suffering infectious diseases up to the resource allocation in the management of an outbreak, are all current activities that can apply artificial intelligence in order to improve their final outcomes.This development has an exponential possibility of application, and is undoubtedly one of the main determinants that will shape medical activity in the future.Notwithstanding the maturation of this technology that is required for its definitive insertion in day-to-day healthcare activities, should be accompanied by definition of reference parameters, validation systems and regulatory guidelines that do not exist yet or are still in its initial stages

Chat GPT: origen, evolución, retos e impactos en la educación / Chat GPT: Origen, Evolution, Challenges and Impacts on Education

Introducción: Los avances de unas tecnologías y la obsolescencia de otras marchan a una velocidad inimaginable, especialmente en este siglo xxi. En los últimos meses de 2022 y primeros meses de 2023 muchas incógnitas y controversias en diferentes campos han surgido en torno a los Chat GPS, una innovación que presenta desafíos nunca pensados para la sociedad actual, así como nuevos retos que impactarán de manera directa en la formación y/o desempeño de profesores, estudiantes, profesionales de la salud, juristas, políticos, informáticos, bibliotecarios, científicos y cualquier ciudadano. Objetivo: Identificar algunas características del chat GPT y su posible impacto en el educación. Posicionamiento de los autores: Se leen en las noticias y reportajes valoraciones de especialistas; se han realizado encuentros virtuales y exposiciones; y están disponibles diversos artículos y videos sobre este tema, algunos llegan a ser elaborados con el propio asistente. Por la novedad del tema, la reciente incorporación como herramienta para el desarrollo profesional, así como por el interés mostrado en los últimos días por la comunidad de profesores de las ciencias médicas cubanas, y considerando que esta herramienta es resultado del desarrollo de la inteligencia artificial, cabe preguntarse: ¿en qué consiste? y ¿cuáles son sus perspectivas? Conclusiones: Resulta oportuno acercarse al tema desde las posibilidades y los retos que abre a la educación y el aprendizaje, en particular a la docencia médica(AU)

Introduction: The advances of some technologies and the obsolescence of others are marching at an unimaginable speed, especially in this twenty-first century. In the last months of 2022 and first months of 2023, many questions and controversies in different fields have arisen with respect to Chat GPT, an innovation that presents challenges never thought of before for today's society, as well as new challenges that will have a direct impact on the training and/or performance of professors, students, health professionals, law practitioners, politicians, computer scientists, librarians, scientists and any citizen. Objective: To identify some technological characteristics of Chat GPT. Positioning of the authors: In news and reports, assessments by specialists are read; virtual meetings and presentations have been held; and several articles and videos on this topic are available, some of them even elaborated by the assistant itself. Due to the novelty of the subject, its recent assimilation as a tool for professional development, as well as the interest shown in recent days by the community of professors of Cuban medical sciences and considering that this tool is the result of the development of artificial intelligence, it is worth wondering what it consists in and what its prospects are. Conclusions: It is appropriate to approach the subject with a focus on the possibilities and challenges that it opens to education and learning (AU)

Tan lejos de la investigación científica, tan cerca de la inteligencia artificial / So far from scientific research, so close to artificial intelligence

En este editorial se exploran los posibles riesgos que representa el uso de la inteligencia artificial para la elaboración de trabajos académicos y científicos. Además, se presenta una lista de riesgos para la investigación científica elaborada por la plataforma ChatGPT con el objetivo de explorar su precisión en la generación de textos.

This editorial explores the possible risks posed by the use of artificial intelligence for the preparation of academic and scientific work. Additionally, a list of risks for scientific research is presented by the ChatGPT platform with the aim of exploring its accuracy in generating texts.

Aprendizado de máquina nos serviços farmacêuticos: uma revisão integrativa / Machine learning in pharmaceutical services: an integrative review

A crescente digitalização e aplicação de inteligência artificial (IA) em problemas complexos do mundo real, tem potencial de melhorar os serviços de saúde, inclusive da atuação dos farmacêuticos no processo do cuidado. O objetivo deste estudo foi identificar na literatura científica, estudos que testam algoritmos de aprendizado de máquina (Machine Learning ­ ML) aplicados as atividades de farmacêuticos clínicos no cuidado ao paciente. Trata-se de uma revisão integrativa, realizada nas bases de dados, Pubmed, Portal BVS, Cochrane Library e Embase. Artigos originais, relacionados ao objetivo proposto, disponíveis e publicados antes de 31 de dezembro de 2021, foram incluídos, sem limitações de idioma. Foram encontrados 831 artigos, sendo 5 incluídos relacionados as atividades inseridas nos serviços de revisão da farmacoterapia (3) e monitorização terapêutica (2). Foram utilizadas técnicas supervisionadas (3) e não supervisionadas (2) de ML, com variedade de algoritmos testados, sendo todos os estudos publicados recentemente (2019-2021). Conclui-se que a aplicação da IA na farmácia clínica, ainda é discreta, sinalizando os desafios da era digital.

The growing application of artificial intelligence (AI) in complex real-world problems has shown an enormous potential to improve health services, including the role of pharmacists in the care process. Thus, the objective of this study was to identify, in the scientific literature, studies that addressed the use of machine learning (ML) algorithms applied to the activities of clinical pharmacists in patient care. This is an integrative review, conducted in the databases Pubmed, VHL Regional Portal, Cochrane Library and Embase. Original articles, related to the proposed topic, which were available and published before December 31, 2021, were included, without language limitations. There were 831 articles retrieved 5 of which were related to activities included in the pharmacotherapy review services (3) and therapeutic monitoring (2). Supervised (3) and unsupervised (2) ML techniques were used, with a variety of algorithms tested, with all studies published recently (2019­2021). It is concluded that the application of AI in clinical pharmacy is still discreet, signaling the challenges of the digital age.

The use of ChatGPT in scientific publishing / O uso do ChatGPT na publicação científica

The use of Generative Pretrained Transformer (ChatGPT), an artificial intelligence tool, for writing scientific articles has been reason for discussion by the academic community ever since its launch in late 2022. This artificial intelligence technology is becoming capable of generating fluent language, and distinguishing between text produced by ChatGPT and that written by people is becoming increasingly difficult. Here, we will present some topics to be discussed: (1) ensuring human verification; (2) establishing accountability rules; (3) avoiding the automatization of scientific production; (4) favoring truly open-source large language models (LLMs); (5) embracing the benefits of artificial intelligence; and (6) broadening the debate. With the emergence of these technologies, it is crucial to regulate, with continuous updates, the development and responsible use of LLMs with integrity, transparency, and honesty in research, along with scientists from various areas of knowledge, technology companies, large research funding bodies, science academies and universities, editors, non-governmental organizations, and law experts

O uso do Generative Pretrained Transformer (ChatGPT), ferramenta de inteligência artificial, na redação de artigos científicos, tem sido motivo de discussão pela comunidade acadêmica desde seu lançamento, no fim de 2022. Essa tecnologia de inteligência artificial está ganhando a capacidade de gerar linguagem fluente, sendo cada vez mais difícil distingui-la dos textos escritos por pessoas. Serão apresentados alguns aspectos para serem debatidos: (1) assegurar a verificação humana; (2) desenvolver regras de responsabilidade; (3) evitar a automatização da produção científica; (4) dar preferência a grandes modelos de linguagem verdadeiramente (LLMs) abertos; (5) abraçar os benefícios da IA; e (6) ampliar o debate. Com o surgimento dessas tecnologias, faz-se necessário regulamentar, com atualização contínua, o desenvolvimento e o uso responsável dos LLMs com integridade, transparência e honestidade na pesquisa, com participação de cientistas de diversas disciplinas, empresas de tecnologia, grandes financiadores de pesquisas, academias de ciências e universidades, editores, organizações não governamentais (ONGs) e especialistas jurídicos

Inteligencia artificial en medicina y procedimientos quirúrgicos: impacto en la toma de decisiones y la salud / Artificial Intelligence in Medicine and Surgical Procedures: Impact on Decision Making and Health

Introducción: Las revisiones sistemáticas de la literatura constituyen una herramienta metodológica práctica para la búsqueda de información sobre investigaciones clínicas, aplicaciones tecnológicas y la toma de decisiones de impacto en la salud. Objetivo: Describir cómo influye la inteligencia artificial en la toma de decisiones médicas según el grado de concordancia entre estas evidencias y los sistemas expertos aplicados en las especialidades clínicas y quirúrgicas de impacto en la salud, según reportes entre 2010 y 2019. Métodos: Se realizó una revisión sistemática con el uso de un modelo de bases de datos relacional y un modelo de entidad relación para garantizar la entidad referencial de la que hacen parte las bases de datos y los artículos, así como la calidad de cada uno de los artículos mediante clasificación por grados de concordancia entre muy concordante o no concordante con la temática de interés y la toma de decisiones de impacto en la salud. Conclusiones: Las aplicaciones como los sistemas expertos, los aprendizajes de máquinas y la robótica aportan innovación a las instituciones y un cambio revolucionario en lo académico, clínico y epidemiológico(AU)

Introduction: Systematic reviews of the literature constitute a practical methodological tool for the search of information on clinical research, technological applications and health impact decision-making. Objectives: To describe how artificial intelligence influences medical decision-making according to the degree of agreement between this evidence and the expert systems applied in clinical and surgical specialties with an impact on health, according to reports from 2010 to 2019. Methods: A systematic review was conducted with the use of a relational database model and a relationship entity model to guarantee the referential entity of which the databases and articles are part, as well as the quality of each of the articles classified by degrees of agreement between very concordant or not concordant with the topic of interest and the decision making of impact on health. Conclusions: Applications such as expert systems, machine learning and robotics bring innovation to institutions and a revolutionary change in academic, clinical and epidemiological areas(AU)

Smartphone-Based Screening for Cardiovascular Diseases: A Trend?

Abstract Cardiovascular diseases are the leading cause of death in the world. People living in vulnerable and poor places such as slums, rural areas and remote locations have difficulty in accessing medical care and diagnostic tests. In addition, given the COVID-19 pandemic, we are witnessing an increase in the use of telemedicine and non-invasive tools for monitoring vital signs. These questions motivate us to write this point of view and to describe some of the main innovations used for non-invasive screening of heart diseases. Smartphones are widely used by the population and are perfect tools for screening cardiovascular diseases. They are equipped with camera, flashlight, microphone, processor, and internet connection, which allow optical, electrical, and acoustic analysis of cardiovascular phenomena. Thus, when using signal processing and artificial intelligence approaches, smartphones may have predictive power for cardiovascular diseases. Here we present different smartphone approaches to analyze signals obtained from various methods including photoplethysmography, phonocardiograph, and electrocardiography to estimate heart rate, blood pressure, oxygen saturation (SpO2), heart murmurs and electrical conduction. Our objective is to present innovations in non-invasive diagnostics using the smartphone and to reflect on these trending approaches. These could help to improve health access and the screening of cardiovascular diseases for millions of people, particularly those living in needy areas.

Clasificación de Imágenes de Neumonía a causa de Covid-19 utilizando Transfer-Learning basado en Redes Convolucionales / Classification of Images of Pneumonia Due to Covid-19 Using TransferLearning, Based on Convolutional Networks

La Inteligencia Artificial ha ayudado a lidiar diferentes problemas relacionados con los datos masivos y a su vez con su tratamiento, diagnóstico y detección de enfermedades como la que actualmente nos preocupa, la Covid-19. El objetivo de esta investigación ha sido analizar y desarrollar la clasificación de imágenes de neumonía a causa de covid-19 para un diagnostico efectivo y óptimo. Se ha usado Transfer-Learning aplicando ResNet, DenseNet, Poling y Dense layer para la elaboración de los modelos de red propios Covid-UPeU y Covid-UPeU-TL, utilizando las plataformas Kaggle y Google colab, donde se realizaron 4 experimentos. El resultado con una mejor clasificación de imágenes se obtuvo en el experimento 4 prueba N°2 con el modelo Covid-UPeU-TL donde Acc.Train: 0.9664 y Acc.Test: 0.9851. Los modelos implementados han sido desarrollados con el propósito de tener una visión holística de los factores para la optimización en la clasificación de imágenes de neumonía a causa de COVID-19(AU)

Artificial Intelligence has helped to deal with different problems related to massive data in turn to the treatment, diagnosis and detection of diseases such as the one that currently has us in concern, Covid-19. The objective of this research has been to analyze and develop the classification of images of pneumonia due to covid-19 for an effective and optimal diagnosis. Transfer-Learning has been used applying ResNet, DenseNet, Poling and Dense layer for the elaboration of the own network models Covid-Upeu and Covid-UpeU-TL, using Kaggle and Google colab platforms, where 4 experiments have been carried out. The result with a better classification of images was obtained in experiment 4 test N ° 2 with the Covid-UPeU-TL model where Acc.Train: 0.9664 and Acc.Test: 0.9851. The implemented models have been developed with the purpose of having a holistic view of the factors for optimization in the classification of COVID-19 images(AU)

On stethoscopes, patient records, artificial intelligence, and zettabytes: A glimpse into the future of digital medicine in Mexico / Sobre estetoscopios, expedientes clínicos, inteligencia artificial y zettabytes: una mirada al futuro de la medicina digital en México

Abstract Science and technology are modifying medicine at a dizzying pace. Although access in our country to the benefits of innovations in the area of devices, data storage and artificial intelligence are still very restricted, the advance of digital medicine offers the opportunity to solve some of the biggest problems faced by medical practice and public health in Mexico. The potential areas where digital medicine can be disruptive are accessibility to quality medical care, centralization of specialties in large cities, dehumanization of medical treatment, lack of resources to access evidence-supported treatments, and among others. This review presents some of the advances that are guiding the new revolution in medicine, discusses the potential barriers to implementation, and suggest crucial elements for the path of incorporation of digital medicine in Mexico.

Resumen La ciencia y la tecnología han modificado la medicina a un ritmo vertiginoso. Si bien el acceso en México a los beneficios de las innovaciones en el área de dispositivos, almacenamiento de datos e inteligencia artificial aún es muy restringido, el avance de la medicina digital ofrece la oportunidad de solventar algunos de los problemas más grandes que enfrenta la práctica médica y la salud pública en este país. Las potenciales áreas en las que la medicina digital puede resultar innovadora son la accesibilidad a cuidados médicos de calidad, la centralización de las especialidades en grandes urbes, la deshumanización del trato médico, la falta de recursos para acceder a tratamientos avalados por evidencia, entre otros. Esta revisión presenta algunos de los avances que guían la nueva revolución en la medicina, revisa el potencial y las posibles barreras para su aplicación, además de sugerir elementos cruciales para el trayecto de incorporación de la medicina digital en México.

Implementation of an Artificial Intelligence Algorithm for sepsis detection / Implantación de Algoritmo de Inteligencia Artificial para la detección de la sepsis / Implantação de algoritmo de inteligência artificial para detecção da sepse

ABSTRACT Objectives: to present the nurses' experience with technological tools to support the early identification of sepsis. Methods: experience report before and after the implementation of artificial intelligence algorithms in the clinical practice of a philanthropic hospital, in the first half of 2018. Results: describe the motivation for the creation and use of the algorithm; the role of the nurse in the development and implementation of this technology and its effects on the nursing work process. Final Considerations: technological innovations need to contribute to the improvement of professional practices in health. Thus, nurses must recognize their role in all stages of this process, in order to guarantee safe, effective and patient-centered care. In the case presented, the participation of the nurses in the technology incorporation process enables a rapid decision-making in the early identification of sepsis.

RESUMEN Objetivos: presentar la experiencia de enfermeros con innovaciones tecnológicas computacionales en el apoyo a la identificación precoz de la sepsis. Métodos: relato de experiencia de pre y post implantación de algoritmos basados en inteligencia artificial para la práctica clínica en un hospital filantrópico, en el primer semestre de 2018. Resultados: describen la motivación para la creación y uso del algoritmo; el papel del enfermero en el desarrollo e implantación de esa tecnología y sus efectos en el proceso de trabajo de la enfermería. Consideraciones Finales: las innovaciones tecnológicas necesitan contribuir a la mejora de las prácticas profesionales en salud, así que los enfermeros deben reconocer su papel en todas las etapas de este proceso, con el fin de garantizar el cuidado seguro, efectivo, centrado en el paciente. En el caso presentado, la participación de los enfermeros en el proceso de incorporación tecnológica potencializa la rápida toma de decisión en la identificación precoz de la sepsis.

RESUMO Objetivos: apresentar a experiência de enfermeiros com inovações tecnológicas computacionais no apoio à identificação precoce da sepse. Métodos: relato de experiência de pré e pós-implantação de algoritmos baseados em inteligência artificial para a prática clínica em um hospital filantrópico, no primeiro semestre de 2018. Resultados: descrevem a motivação, para criação e uso do algoritmo, o papel do enfermeiro no desenvolvimento e na implantação dessa tecnologia e os seus efeitos no processo de trabalho da enfermagem. Considerações Finais: inovações tecnológicas precisam contribuir para a melhoria das práticas profissionais em saúde. Assim, enfermeiros devem reconhecer seu papel em todas as etapas desse processo, de modo a garantir o cuidado seguro, efetivo, centrado no paciente. No caso apresentado, a participação dos enfermeiros no processo de incorporação tecnológica potencializa a rápida tomada de decisão na identificação precoce da sepse.

Artificial intelligence in the diagnosis of cardiovascular disease

SUMMARY Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enabling cost-effectiveness, and reducing readmission and mortality rates. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI's application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine.

RESUMO A inteligência artificial (IA) é um campo da ciência da computação que tem como objetivo imitar os processos de pensamento humano. Técnicas de IA têm sido aplicadas na medicina cardiovascular para explorar novos genótipos e fenótipos em doenças existentes, melhorar a qualidade do atendimento ao paciente, possibilitar custo-efetividade e reduzir taxas de readmissão e mortalidade. Existe um grande potencial da IA na medicina cardiovascular; no entanto, a ignorância dos desafios pode ofuscar seu impacto clínico. Esse artigo fornece a aplicação da IA no atendimento clínico cardiovascular e discute seu papel potencial na facilitação da medicina cardiovascular de precisão.

Horizonte de la inteligencia artificial y neurociencias: Acerca de robots, androides y cyborgs / Horizon of artificial intelligence and neurosciences. About robots, androids and cyborgs

La inteligencia artificial permite que los procesos cerebrales sean analizados como procesos computacionales. Presenta dos líneas inquietantes: el Proyecto Robot, llamado androide cuando es antropomórfico, y el Proyecto Cyborg. Los robots están destinados a tareas repetitivas, riesgosas o de precisión, en las que pueden superar las limitaciones humanas, no percibiéndose conflictos éticos aunque sí nuevos desafíos en la organización social. Respecto de los androides, más allá de sus capacidades, habrá que considerar los efectos que puedan ocurrir en el ser humano durante la interacción con la máquina, como el impacto de la mímica androide sobre la emoción y estado de ánimo. Los cyborgs son criaturas compuestas por elementos orgánicos y cibernéticos cuya finalidad es emular o mejorar las capacidades de la parte orgánica. No se reconoce conflicto en su empleo para rehabilitación o para suplir funciones alteradas o ausentes; aspectos negativos serían su uso para la manipulación. Otra aplicación del proyecto cyborg a considerar es el enhancement, término utilizado en la literatura anglosajona para definir el aumento de facultades neurocognitivas o sensoriales mediante la estimulación transcraneal o intracraneal. El conflicto neuroético surge porque el objetivo no es curar sino la perfectibilidad, o nuevas modalidades de percepción. Los profesionales de la salud deben actuar en un entorno nuevo y cambiante que trasciende las neurociencias y la salud pública. El progreso continúa; por lo que se debe informar a la sociedad, anticipar dilemas, y ofrecer espacios de reflexión para la toma de decisiones individuales y para la especie humana.

Artificial intelligence permits cerebral processes to be analyzed like computing processes. We can recognize two disturbing lines we can call: The Robot Project, android when is anthropomorphic, and The Cyborg Project. Robots are destined to perform repetitive, risky or accurate tasks in which they can surpass human limitations. No ethical conflicts are perceived here but there are new challenges to be faced as far as the social organization is concerned. As regards androids, apart from their robotic capabilities, their effect on the human being during interaction should be considered, as the impact of mimic's android on the emotion. The cyborgs are creatures composed by biological and cybernetic elements whose goal is to improve the capabilities of their biological parts. There has been no evidence of conflict in their use for rehabilitation or to supply impaired or non-existing functions. It would be different if they were used for manipulative activities. Another application of the cyborg project to consider is the term "enhancement", used to describe the increase of neurocognitive or sensory faculties through transcranial/intracranial stimulation. The ethical conflict here lies in the fact that the focus is not so much on healing but on seeking perfectibility or new modalities of perception. Health professionals must act in a new and constantly changing environment that transcends neurosciences and public health. Progress never stops; so, society have to be informed, anticipate dilemmas, and make room for reflection to help decision-making processes that involve individuals as well as the whole human species.