Agent based decision support systems in medicine

Embedding Machine Learning technology into Agent Driven Diagnosis Systems adds a new potential to the realm of Medicine, and in particular to the imagiology one. However, despite all the research done in the last years on the development of new methodologies for problem solving, in terms of the design of MultiAgent Systems (MAS) there is none where both the agent and the organizational view can be modelled. Current multi-agent approaches to problem solving either take a centralist, static approach to organizational design or take an emergent view in which agent interactions are not pre-determined, thus making it impossible to make any predictions on the behavior of the whole systems. Most of them also lack a model of the norms in the environment that should rule the behaviour of the agent society as a whole and/or the actions of the individuals. In this paper, it is proposed not only a framework for modelling and run agent organizations, but also to depict the different components of such societies. To illustrate these premises, we will evoke a society with one modality, the Axial Computed Tomography one, where two different but complementary computational paradigms, the Artificial Neural Networks and the Case Based Reasoning are object of attention

Health data management in the medical arena

In this paper it is presented an Agency for Integration, Archive and Diffusion of Medical Information (AIDA), which configures a data warehouse, developed using Multi-Agent technology. AIDA is like a symbiont, with a close association with core applications present at any health care facility, such as the Picture Archive Communication System, the Radiological Information System or the Electronic Medical Record Information System. Multi-Agent Systems also configure a new methodology for problem solving

Data warehousing through multi-agent systems in the medical arena

Comunicação apresentada na International Conference on Knowledge Engineering and Decision Support, 1, Porto, 2004.In this paper it is presented AIDA, an Agency for Integration, Archive and Diffusion of Medical Information. It configures a data warehouse, developed using Multi-Agent technology, that integrates and archives information from heterogeneous sources of a health care unit. AIDA is like a symbiont, with a close association with core applications at any health care facility, namely the Picture Archive Communication System, the Radiological Information System and the Electronic Medical Record Information System, that are built upon pro-active agents and communicate with the AIDA’s ones

Agent driven diagnosis in medicine

Embedding Machine Learning technology into Agent Driven Diagnosis Systems adds a new potential to the realm of Medicine, and in particular to the imagiology one. However, despite all the research done in the last years on the development of methodologies for designing MultiAgent Systems (MAS), there is no methodology suitable for the specification and design of MAS in complex domains where both the agent view and the organizational view can be modelled. Current multi-agent approaches either take a centralist, static approach to organizational design or take an emergent view in which agent interactions are not pre-determined, thus making it impossible to make any predictions on the behavior of the whole systems. Most of them also lack a model of the norms in the environment that should rule the behavior of the agent society as a whole and/or the actions of individuals. In this paper, we propose a framework for modelling agent organizations, and we illustrate the different components of a society with one modality, the Axial Computed Tomography scenario, combining two methodologies for problem solving, the Artificial Neural Networks and the Case Based Reasoning ones

A web-based collaboration approach for teaching in medicine

Teaching medicine requires developing a vast range of manual, intellectual, visual and tactile skills as well as taking into account large amounts of factual information. Traditional medical teaching and individual learning in particular, can be complemented with electronic web based systems. One of the main impacts of e-Teaching in education resides in the fact that it provides opportunities to create resources that turn the learning process flexible. This implies a different relation between teachers and students and even between institutions, in the sense that the students participate on their own formation and the vertical hierarchy tends to become increasingly more horizontal. Awareness of the knowledge constructing process is increased, and consequently more satisfaction gained from learning. In this paper we describe a webbased collaboration approach for teaching that is being developed to simulate conversational dialogue in the area of Medicine, that enables the integration of highly heterogeneous sources of information into a coherent knowledge base accessed from web-based interfaces, either from the tutor’s point of view or the development of the discipline in itself, i.e. the system’s content is created automatically by the physicians as their daily work goes on

Enhanced photocatalytic activity of Au/TiO2 nanoparticles against ciprofloxacin

In the last decades, photocatalysis has arisen as a solution to degrade emerging pollutants such as antibiotics. However, the reduced photoactivation of TiO2 under visible radiation constitutes a major drawback because 95% of sunlight radiation is not being used in this process. Thus, it is critical to modify TiO2 nanoparticles to improve the ability to absorb visible radiation from sunlight. This work reports on the synthesis of TiO2 nanoparticles decorated with gold (Au) nanoparticles by deposition-precipitation method for enhanced photocatalytic activity. The produced nanocomposites absorb 40% to 55% more radiation in the visible range than pristine TiO2, the best results being obtained for the synthesis performed at 25 °C and with Au loading of 0.05 to 0.1 wt. %. Experimental tests yielded a higher photocatalytic degradation of 91% and 49% of ciprofloxacin (5 mg/L) under UV and visible radiation, correspondingly. Computational modeling supports the experimental results, showing the ability of Au to bind TiO2 anatase surfaces, the relevant role of Au transferring electrons, and the high affinity of ciprofloxacin to both Au and TiO2 surfaces. Hence, the present work represents a reliable approach to produce efficient photocatalytic materials and an overall contribution in the development of high-performance Au/TiO2 photocatalytic nanostructures through the optimization of the synthesis parameters, photocatalytic conditions, and computational modeling.This work was supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the strategic projects UID/FIS/04650/2013 by Fundo Europeu de Desenvolvimento Regional (FEDER) funds through the COMPETE 2020—Programa Operacional Competitividade e Internacionalização (POCI) with the reference project POCI-01-0145-FEDER-006941, project PTDC/CTM-ENE/5387/2014, as well as UID/BIO/04469 unit through COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. P.M. Martins thanks the FCT for the grant SFRH/BD/98616/2013 and Luciana Pereira for the grant SFRH/BPD/110235/2015. M. Melle-Franco would like to acknowledge support from Centro de Investigação em Materiais Cerâmicos e Compósitos (CICECO)—Aveiro Institute of Materials, POCI-01-0145-FEDER007679 (UID/CTM/50011/2013) and the FCT (IF/00894/2015).info:eu-repo/semantics/publishedVersio

Multi-agent system for multimodal machine learning object detection

Multi-agent systems have shown great promise in addressing complex problems that traditional single-agent approaches are not be able to handle. In this article, we propose a multi-agent system for the conception of a multimodal machine learning problem on edge devices. Our architecture leverages docker containers to encapsulate knowledge in the form of models and processes, enabling easy management of the system. Communication between agents is facilitated by Message Queuing Telemetry Transport, a lightweight messaging protocol ideal for Internet of Things and edge computing environments. Additionally, we highlight the significance of object detection in our proposed system, which is a crucial component of many multimodal machine learning tasks, by enabling the identification and localization of objects within diverse data modalities. In this manuscript an overall architecture description is performed, discussing the role of each agent and the communication protocol between them. The proposed system offers a general approach to multimodal machine learning problems on edge devices, demonstrating the advantages of multi-agent systems in handling complex and dynamic environments.This work has been supported by FCT (Fundação para a Ciência e Tecnologia) within the R&D Units Project Scope: UIDB/00319/2020

Ad5/3 is able to avoid neutralization by binding to erythrocytes and lymphocytes

Oncolytic adenoviruses are promising cancer therapeutic agents. Clinical data have shown adenoviruses' ability to transduce tumors after systemic delivery in human cancer patients, despite antibodies. In the present work, we have focused on the interaction of a chimeric adenovirus Ad5/3 with human lymphocytes and human erythrocytes. Ad5/3 binding with human lymphocytes and erythrocytes was observed to occur in a reversible manner, which allowed viral transduction of tumors, and oncolytic potency of Ad5/3 in vitro and in vivo,with or without neutralizing antibodies. Immunodeficient mice bearing xenograft tumors showed enhanced tumor transduction following systemic administration, when Ad5/3 virus was bound to lymphocytes or erythrocytes (P <0.05). In conclusion, our findings reveal that chimeric Ad5/3 adenovirus reaches non-injected tumors in the presence of neutralizing antibodies: it occurs through reversible binding to lymphocytes and erythrocytes.Peer reviewe