Analysis of mobile applications that help skin care through facial recognition: A systematic analysis

The knowledge and integration of new technologies has shown that it is possible to improve access to health services, such as skin care and diagnosis of pathologies in the area of dermatology, applying mobile technologies and ap- plications. In this systematic review it seeks to investigate mobile applications that use intelligent systems that help skin care through facial recognition. The investigation was carried out between 2010 and 2018, finding 168 articles that resemble the subject; that were reduced to 28 articles with available text, after a dissertion of articles that did not contribute to the research as well as repeated. Finally, three of them were chosen to begin the topic of study. The present review allows us to conclude that there is a guideline for using mobile applications and technologies for the care and diagnosis of pathologies on the skin by means of algorithms, models, techniques and methods applying intelligent systems. How- ever, the integration of mobile applications directly for skin care is just beginning the research field, but offers promising processes and results. Resumen. El conocimiento e integración de nuevas tecnologías, ha demostrado que se puede mejorar el acceso a servicios de la salud, como es al cuidado de la piel  y diagnóstico de patologías en el área de la dermatología, aplicando tecnologías  y aplicaciones móviles. En esta revisión sistemática busca indagar aplicaciones móviles que usan sistemas inteligentes que ayuden al cuidado de la piel mediante reconocimiento facial. La indagación fue realizada entre 2010 y 2018, encontrando 168 artículos que se asemejan al tema; que se redujeron a 28 artículos con texto disponible, luego de una dicersion de artículos que no aportaban a la investigación como también repetidos. Finalmente, tres de ellos se eligió para empezar el tema  de estudio. La presente revisión permite concluir que hay una directriz para usar aplicaciones y tecnologías móviles para el cuidado y el diagnostico de patologías sobre la piel mediante algoritmos, modelos, técnicas y métodos aplicando sistemas inteligentes. Sin embargo, la integración de aplicaciones móviles directamente para elcuidado de la piel, apenas inicia el campo de investigación, pero ofrece procesos y resultados prometedores

Accelerated Forgetting in People with Epilepsy: Pathologic Memory Loss, Its Neural Basis, and Potential Therapies

While forgetting is vital to human functioning, delineating between normative and disordered forgetting can become incredibly complex. This thesis characterizes a pathologic form of forgetting in epilepsy, identifies a neural basis, and investigates the potential of stimulation as a therapeutic tool. Chapter 2 presents a behavioral characterization of the time course of Accelerated Long-Term Forgetting (ALF) in people with epilepsy (PWE). This chapter shows evidence of ALF on a shorter time scale than previous studies, with a differential impact on recall and recognition. Chapter 3 builds upon the work in Chapter 2 by extending ALF time points and investigating the role of interictal epileptiform activity (IEA) in ALF. These findings lend support for distinct forgetting patterns between recall and recognition memory. We also demonstrate the contribution of hippocampal IEA during slow-wave sleep to this aberrant forgetting. Chapter 4 investigates the potential of intracranial stimulation to ameliorate IEA burden. Our findings suggest that stimulation does not appear to have a direct effect on IEA rate. Further studies are necessary to explore the potential of stimulation as a therapeutic tool outside of seizure cessation. Overall, this thesis provides further evidence and classification of long-term memory impairment in epilepsy and identifies a neural correlate that can be targeted for future clinical intervention

TOPOLOGICAL PROPERTIES OF A NETWORK OF SPIKING NEURONS IN FACE IMAGE RECOGNITION

We introduce a novel system for recognition of partially occluded and rotated images. The system is based on a hierarchical network of integrate-and-fire spiking neurons with random synaptic connections and a novel organization process. The network generates integrated output sequences that are used for image classification. The network performed satisfactorily given appropriate topology, i.e. the number of neurons and synaptic connections, which corresponded to the size of input images. Comparison of Synaptic Plasticity Activity Rule (SAPR) and Spike Timing Dependant Plasticity (STDP) rules, used to update connections between the neurons, indicated that the SAPR gave better results and thus was used throughout. Test results showed that the network performed better than Support Vector Machines. We also introduced a stopping criterion based on entropy, which significantly shortened the iterative process while only slightly affecting classification performance