Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Artificial intelligence within the interplay between natural and artificial computation:Advances in data science, trends and applications

Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.BMS - Pfizer(U01 AG024904). Spanish Ministry of Science, projects: TIN2017-85827-P, RTI2018-098913-B-I00, PSI2015-65848-R, PGC2018-098813-B-C31, PGC2018-098813-B-C32, RTI2018-101114-B-I, TIN2017-90135-R, RTI2018-098743-B-I00 and RTI2018-094645-B-I00; the FPU program (FPU15/06512, FPU17/04154) and Juan de la Cierva (FJCI-2017–33022). Autonomous Government of Andalusia (Spain) projects: UMA18-FEDERJA-084. Consellería de Cultura, Educación e Ordenación Universitaria of Galicia: ED431C2017/12, accreditation 2016–2019, ED431G/08, ED431C2018/29, Comunidad de Madrid, Y2018/EMT-5062 and grant ED431F2018/02. PPMI – a public – private partnership – is funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbott, Biogen Idec, F. Hoffman-La Roche Ltd., GE Healthcare, Genentech and Pfizer Inc

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Tratamiento con endoprótesis y espirales de un pseudoaneurisma asociado a una estenosis

Propósito. Comunicar nuestra experiencia en el tratamiento de un paciente con un pseudoaneurisma asociado a una estenosis post-disección en la arteria carótida interna cervical. Caso clínico. Paciente de 45 años valorado en el servicio de urgencias por hemiparesia izquierda. Entre sus antecedentes destacaba ser fumador importante, hipertensión arterial, hipercolesterolemia, peritonitis a los 18 años e infarto de miocardio hace un año. Tras la realización de TC y RM, en una angiografía cerebral se diagnosticó una oclusión de la arteria carótida interna derecha, presentando en la izquierda una estenosis asociada a un pseudoaneurisma. Mediante abordaje femoral común derecho, se realizó un implante de una endoprótesis metálica en la zona estenótica; a través de la malla de la misma, se excluyó el pseudoaneurisma con espirales metálicos. Conclusión. Este caso muestra la posibilidad de recuperar la luz de una zona estenótica de la arteria carótida interna con una endoprótesis metálica no cubierta y simultáneamente embolización a su través de una zona pseudoaneurismática sin riesgo de migración

Achados de imagem e alternativas terapêuticas das malformações vasculares periféricas Imaging findings and therapeutic alternatives for peripheral vascular malformations

As malformações vasculares periféricas compreendem um espectro de lesões que se tornam aparentes no decorrer da vida e podem ser encontradas em praticamente todo o corpo. São pouco comuns e frequentemente confundidas com o hemangioma infantil. Estas doenças são completamente distintas tanto em relação à história clínica como ao prognóstico e às formas de tratamento. Nestas lesões, a história evolutiva e as características do exame físico são de extrema importância para o adequado diagnóstico clinicorradiológico, que guiará a melhor alternativa terapêutica. As classificações mais recentes dividem as malformações vasculares periféricas levando em consideração o fluxo sanguíneo (alto e baixo) e os componentes vasculares envolvidos (arteriais, capilares, linfáticos e venosos). As malformações vasculares periféricas representam um desafio diagnóstico e terapêutico, e exames complementares como tomografia computadorizada, ultrassonografia com Doppler e ressonância magnética, em conjunto com a história clínica, podem trazer informações quanto às características de fluxo e à extensão das lesões. Arteriografia e flebografia confirmam o diagnóstico, avaliam a sua extensão e orientam a decisão terapêutica. Malformações de baixo fluxo geralmente são tratadas por abordagem percutânea e injeção de agente esclerosante, enquanto para as malformações de alto fluxo o acesso é endovascular com uso de agentes embolizantes permanentes líquidos ou sólidos.<br>Peripheral vascular malformations represent a spectrum of lesions that appear through the lifetime and can be found in the whole body. Such lesions are uncommon and are frequently confounded with infantile hemangioma, a common benign neoplastic lesion. In the presence of such lesions, the correlation between the clinical and radiological findings is extremely important to achieve a correct diagnosis, which will guide the best therapeutic approach. The most recent classifications for peripheral vascular malformations are based on the blood flow (low or high) and on the main vascular components (arterial, capillary, lymphatic or venous). Peripheral vascular malformations represent a diagnostic and therapeutic challenge, and complementary methods such as computed tomography, Doppler ultrasonography and magnetic resonance imaging, in association with clinical findings can provide information regarding blood flow characteristics and lesions extent. Arteriography and venography confirm the diagnosis, evaluate the lesions extent and guide the therapeutic decision making. Generally, low flow vascular malformations are percutaneously treated with sclerosing agents injection, while in high flow lesions the approach is endovascular, with permanent liquid or solid embolization agents