Artificial intelligence in healthcare delivery: Prospects and pitfalls

This review provides a comprehensive examination of the integration of Artificial Intelligence (AI) into healthcare, focusing on its transformative implications and challenges. Utilising a systematic search strategy across electronic databases such as PubMed, Scopus, Embase, and ScienceDirect, relevant peer-reviewed articles published in English between January 2010 till date were identified. Findings reveal AI's significant impact on healthcare delivery, including its role in enhancing diagnostic precision, enabling treatment personalisation, facilitating predictive analytics, automating tasks, and driving robotics. AI algorithms demonstrate high accuracy in analysing medical images for disease diagnosis and enable the creation of tailored treatment plans based on patient data analysis. Predictive analytics identify high-risk patients for proactive interventions, while AI-powered tools streamline workflows, improving efficiency and patient experience. Additionally, AI-driven robotics automate tasks and enhance care delivery, particularly in rehabilitation and surgery. However, challenges such as data quality, interpretability, bias, and regulatory frameworks must be addressed for responsible AI implementation. Recommendations emphasise the need for robust ethical and legal frameworks, human-AI collaboration, safety validation, education, and comprehensive regulation to ensure the ethical and effective integration of AI in healthcare. This review provides valuable insights into AI's transformative potential in healthcare while advocating for responsible implementation to ensure patient safety and efficacy

La simulación social, ¿una nueva manera de investigar en ciencia social?

Este artículo ofrece un sucinto panorama de la simulación social, presentándola como un medio para modelar los procesos sociales y como un instrumento para la investigación social. En la introducción, se definen conceptos clave como modelo, modelo matemático, simulación social e inteligencia artificial social. En la segunda parte, se muestra la extensa variedad de modelos de inteligencia artificial social y sus aplicaciones, tanto a partir de la simulación clásica como en sus nuevas manifestaciones. Finalmente, se brindan algunas reflexiones de carácter más metodológico sobre la simulación social.This papers offers a brief review of the social simulation, which can he considered a way to model social processes, and also as an instrument for sociological research. First of all, key concepts such that model, mathematical model, social simulation and social artificial intelligence are defined. Secondly, a variety of models of social artificial intelligence and its applications are displayed. Finally, there are some methodological consideration about social simulation

Computação na medicina: a técnica de raciocínio baseado em casos temporais no auxílio ao diagnóstico / Computing and medicine: temporal case based reasoning applied in support to diagnosis

O Raciocínio Baseado em Casos (RBC) é uma técnica de Inteligência Artificial aplicada em diversas áreas e que vem sendo considerada nos últimos anos no apoio ao diagnóstico médico. Seu uso nesse contexto depende de algumas modificações não triviais, em razão da dependência dos dados em relação à variável tempo. Este trabalho examina os pontos principais desse problema, destacando soluções da literatura e apontando perspectivas a serem exploradas.

A Comparative Analysis of Design Techniques for the Construction of an Expert System for Aircraft Engine Diagnostics

The lack of knowledge and understanding of diagnostic aircraft propulsion systems causes inappropriate problem diagnosis. Because of increasing complexity, technicians are incapable of performing the necessary tasks in accordance with standard regulations. More sophisticated systems are needed today to assist the user technician in decision-making. This work provided a study of rule-based and frame-based expert system techniques to determine the most appropriate solution in the domain of complex diagnosis using large amounts of deterministic data. The study produced a framework that facilitates the diagnosing of faults on aircraft engines, thus reducing the burden on the aircraft mechanic regardless of experience level. An intelligent system, the Virtually Automated Maintenance Analysis System (V AMAS), was created as a test model. It was used to compare the relative efficiency of the different expert systems techniques and the effectiveness of expert systems. One aviation malfunction problem was identified. Information collected for the Main Ignition Malfunction was developed into question sets and coded. Six specific subsets of problems were addressed. This research compared the rule-based and frame-based knowledge representation techniques using a set of evaluation factors: computational efficiency, correctness, expressiveness, and consistency. From the analysis it was concluded that the frame based knowledge representation technique ranked higher than the rule-based representation, and is suitable for use with an expert system to represent an aircraft propulsion system \u27s deterministic data

Artificial Intelligence in Healthcare Delivery: Prospects and Pitfalls

This review provides a comprehensive examination of the integration of Artificial Intelligence (AI) into healthcare, focusing on its transformative implications and challenges. Utilising a systematic search strategy across electronic databases such as PubMed, Scopus, Embase, and Sciencedirect, relevant peer-reviewed articles published in English between January 2010 till date were identified. Findings reveal AI's significant impact on healthcare delivery, including its role in enhancing diagnostic precision, enabling treatment personalisation, facilitating predictive analytics, automating tasks, and driving robotics. AI algorithms demonstrate high accuracy in analysing medical images for disease diagnosis and enable the creation of tailored treatment plans based on patient data analysis. Predictive analytics identify high-risk patients for proactive interventions, while AI-powered tools streamline workflows, improving efficiency and patient experience. Additionally, AI-driven robotics automate tasks and enhance care delivery, particularly in rehabilitation and surgery. However, challenges such as data quality, interpretability, bias, and regulatory frameworks must be addressed for responsible AI implementation. Recommendations emphasise the need for robust ethical and legal frameworks, human-AI collaboration, safety validation, education, and comprehensive regulation to ensure the ethical and effective integration of AI in healthcare. This review provides valuable insights into AI's transformative potential in healthcare while advocating for responsible implementation to ensure patient safety and efficacy

Impact assessment of AI-enabled automation on the workplace and employment. The case of Portugal

Artificial intelligence (AI) has the potential to lead to a wave of innovation in organiza-tional design, changes in the workplace and create disruptive effects in the employment sys-tems across the world. Moreover, the future deployment of broad-spectrum algorithms capa-ble of being used in wide areas of application (e.g., industrial robotics, software and data anal-ysis, decision-making) can lead to considerable changes in current work patterns, swiftly render many unemployed across the globe and profoundly destabilize labour relations. The impacts of AI are estimated to lead to a reduction of millions of workplaces. But qualitative research about AI and its governance is scarce. An emergent technology requires a technology assess-ment (TA) approach to understand the implications of AI in firms. Mechanisms of industrial democracy can help to adopt AI by ensuring adequate arrangements for employees and avoid-ing conflicts (mitigating negative effects, promoting reskilling, etc.). In this research work, the probable penetration of AI in the manufacturing sector is identified to study its effects in work organization and employment in Portugal. Is the employ-ment changing alongside recent AI trends in Portugal? What are the expectable changes in work organisation due to AI-enabled automation? Are there signs of work qualification to go with AI systems implementation? Are there visions on the role of humans on the interaction with the features of industry 4.0? Does that imply new forms of human interaction with AI? These are the questions this research work will try to answer. A TA approach using mixed methods was applied to conduct statistical analyses of relevant databases, interviews with ac-ademic, industrial and social actors and exploratory scenarios of AI-based automation systems, on work organization and employment. The manufacturing industry was the chosen sector since it is the sector where most cases of AI-based automation systems are in place. Findings suggest that, until now, it seems AI is still not able to replace most of the human skills and cognitive capacities but can replace humans on simple tasks. In the future, four different possible states may occur, according to the various initial conditions, the com-pany's motivation, their business strategy, the public policies in place and main social actors involved: Re-organisation of work; Substitution of the workforce; People at the centre and Fo-cus on Efficiency. These were the basis for our scenario outcomes.A inteligência artificial (IA) tem o potencial de levar a uma onda de inovação no desenho das organizações, nas mudanças no local de trabalho e em criar efeitos disruptivos nos sistemas de emprego em todo o mundo. Além disso, a futura implementação de algoritmos de amplo espectro, capazes de serem usados em muitas áreas de aplicação (por exemplo, robótica industrial, software e análise de dados, tomada de decisão), pode levar a mudanças consideráveis nos padrões de trabalho atuais, e rapidamente, levar ao desemprego em todo o mundo e à desestabilização profunda das relações laborais. Estima-se que os impactos da IA levem a uma redução de milhões de locais de trabalho. Mas a investigação qualitativa sobre IA é escassa. Uma tecnologia emergente requer uma abordagem de avaliação de tecnologia (AT) para entender as suas implicações. Mecanismos de democracia industrial podem ajudar a adotar a IA, garantindo condições adequadas para os trabalhadores e evitando conflitos (mitigando efeitos negativos, promovendo requalificação, etc.). Neste trabalho de investigação identifica-se a provável penetração da IA no setor da indústria transformadora para estudar os seus efeitos na organização do trabalho e emprego em Portugal. O emprego está a mudar a par das tendências recentes da IA em Portugal? Quais são as mudanças na organização do trabalho devido à automação baseada em IA? Há indícios de qualificação do trabalho para acompanhar a implementação dos sistemas de IA? Existem visões sobre o papel do ser humano na interação com os recursos da indústria 4.0? Isso implica novas formas de interação humana com a IA? Estas são as perguntas que este trabalho de investigação tentará responder. Na abordagem de AT, foram usados métodos mistos para realizar análises estatísticas de bases de dados, entrevistas com atores do ecossistema académico, industrial e social e cenários exploratórios sobre os efeitos da adoção de sistemas de automação baseados em IA, na organização do trabalho e emprego. A indústria transformadora foi escolhida por ser onde existem a maioria de casos de aplicação de sistemas de auto-mação baseados em IA. Os resultados sugerem que, até ao momento, que a IA não tem a capacidade de subs-tituir a maioria das competências e raciocínio humanos, mas apenas tarefas simples. No futuro, poderão ocorrer quatro situações, dependendo das condições iniciais, motivação e estratégia da empresa, das políticas e incentivos públicos existentes e do envolvimento de atores sociais: Reorganização do trabalho; Substituição da mão-de-obra; Pessoas no centro da transformação e foco na Eficiência. Estas foram a base para os nossos cenários de referência