
Margarita-Arimatea Diaz-CortesClick Therapeutics Inc. · Discovery and Translational Science
Margarita-Arimatea Diaz-Cortes
Doctor
About
37
Publications
8,390
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476
Citations
Introduction
Additional affiliations
October 2018 - July 2021
February 2013 - September 2015
Education
April 2016 - July 2019
August 2012 - July 2014
August 2008 - July 2012
University of Guadalajara
Field of study
- Biomedical Engineering
Publications
Publications (37)
Introduction:
Computational brain network modeling using The Virtual Brain (TVB) simulation platform acts synergistically with machine learning (ML) and multi-modal neuroimaging to reveal mechanisms and improve diagnostics in Alzheimer's disease (AD).
Methods:
We enhance large-scale whole-brain simulation in TVB with a cause-and-effect model lin...
Background
Comprehensive knowledge bases as NeuroMMSig, a knowledge base of multimodal mechanistic signatures, catalog knowledge about Alzheimer's Disease (AD) and its underlying candidate mechanisms. Besides, digital atlases provide information about cytoarchitectonics and receptor densities, e.g. JuBrain at the EBRAINS platform of the Human Brain...
INTRODUCTION
Computational brain network modeling using The Virtual Brain (TVB) simulation platform acts synergistically with machine learning and multi-modal neuroimaging to reveal mechanisms and improve diagnostics in Alzheimer’s disease.
METHODS
We enhance large-scale whole-brain simulation in TVB with a cause-and-effect model linking local Amy...
Introduction: While the prevalence of neurodegenerative diseases associated with dementia such as Alzheimer's disease (AD) increases, our knowledge on the underlying mechanisms, outcome predictors, or therapeutic targets is limited. In this work, we demonstrate how computational multi-scale brain modeling links phenomena of different scales and the...
Introduction: While the prevalence of neurodegenerative diseases associated with dementia such as Alzheimer's disease (AD) increases, our knowledge on the underlying mechanisms, outcome predictors, or therapeutic targets is limited. In this work, we demonstrate how computational multi-scale brain modelling links phenomena of different scales and th...
Corner detection represents one of the most important steps to identify features in images. Due to their powerful local processing capabilities, Cellular Nonlinear/Neural Networks (CNN) are commonly utilized in image processing applications such as image edge detection, image encoding and image hole filling. CNN perform well for locating corner fea...
Breast cancer is one of the most common diseases and the second cause of death in women around the world. The presence of a cancerous tumor increase temperature in the region near to it, such heating is then transferred to the skin surface. In this sense, screening seeks to help in cancer diagnostic process before symptoms became evident in a perso...
The main objective of multi-modal optimization is to find multiple global and local optima for a problem in only one execution. Detecting multiple solutions to a multi-modal optimization formulation is especially useful in engineering, since the best solution could not represent the best realizable due to various practical restrictions. The States...
Many processes are too complex to be manipulated quantitatively; however, humans succeed by using simple rules of thumb that are extracted from their experiences. Fuzzy logic emulates the human reasoning in the use of imprecise information to generate decisions. Unlike traditional approaches, which require a mathematical understanding of the system...
Pattern Detection (PD) plays an important role in several image processing applications such as feature tracking, object recognition, stereo matching and remote sensing. PD involves two critical aspects: similarity measurement and search strategy. The simplest available PD method finds the best possible coincidence between the images through an exh...
Color segmentation in digital images is a challenging task due to image capture conditions. Typical segmentation algorithms present several difficulties in this process because they do not tolerate variations in color hue corresponding to the same object. In this chapter is presented an approach for color segmentation based on learning vector quant...
Electromagnetism-like optimization (EMO) is a global optimization algorithm which allows to solve complex multimodal optimization problems. EMO employs search agents that emulate a population of charged particles which interact to each other according to electromagnetism’s laws (attraction and repulsion). Traditionally, EMO requires a large number...
Induction motors represent the main component in most of the industries. Induction motors represent the main component in most of the industries. They use the biggest energy percentages in industrial facilities. This consume depends on the operation conditions of the induction motor imposed by its internal parameters. In this approach, the paramete...
Multi-threshold selection for image segmentation is considered as a critical pre-processing step for image analysis, pattern recognition and computer vision. This chapter explores the use of the Learning Automata (LA) algorithm to compute the thresholding points for segmentation proposes. LA is a heuristic method which is able to solve complex opti...
Planning Control uses information regarding a problem and its environment to decide whether one plan is better than other in order to reach a required control objective. An interesting alternative for planning control is model predictive control (MPC) and the receding horizon control. MPC is the planning approach that has recently found a wide acce...
Image segmentation is a very important task in Computer Vision community, due to its capabilities for further steps that lead to recognizing patterns in digital images. Thus, the process of thresholding selection has become an interesting area, in recent years this procedure has been investigated as an optimization problem. On the other Hand, ABC i...
Corner detection is an important task in computer vision problems due to the complexity of determinate the shape of different regions within an image. Real-life image data are always inexact due to inherent uncertainties that may arise from the imaging capture process such as defocusing, illumination changes, noise, etc. Therefore, the localization...
Motion estimation is one of the major problems in developing video coding applications. Motion estimation is one of the major problems in developing video coding applications. On the other hand, block-matching (BM) algorithms are the most popular methods due to their effectiveness and simplicity for both software and hardware implementations. A BM...
Automatic circle detection in digital images is considered an important and complex task for the computer vision community. Consequently, recently, a tremendous amount of research has been devoted to find an optimal circle detector. This chapter presents an algorithm for the automatic detection of circular shapes from complicated and noisy images w...
Real-time gaze control is a complicated task because it considers different dynamics behaviors of the elements involved in the process. This chapter describes the use of the adaptive network-based fuzzy inference system (ANFIS) model to reduce the delay effects in gaze control. The approach considers the modelling of the target objet location to pr...
This book bridges the gap between Soft Computing techniques and their applications to complex engineering problems. In each chapter we endeavor to explain the basic ideas behind the proposed applications in an accessible format for readers who may not possess a background in some of the fields. Therefore, engineers or practitioners who are not fami...
The ability of an Evolutionary Algorithm (EA) to find a global optimal solution depends on its capacity to find a good relation between exploitation of the found-so-far elements and exploration of the search space. Inspired by natural phenomena, researchers have developed many successful evolutionary algorithms. In their original versions, such app...
Allostasis is a biological term recently coined which explains how the modifications of specialized organ conditions inside the body allow to achieve stability when an unbalance condition is presented. In this chapter, a biologically-inspired algorithm, namely Allostatic Optimization (AO) is proposed for solving optimization tasks. The AO algorithm...
In this chapter, a metaheuristic algorithm for global optimization called the Collective Animal Behavior (CAB) is introduced. The algorithm is based on animal groups, such as schools of fish, flocks of birds, swarms of locusts, and herds of wildebeest, that exhibit a variety of behaviors including swarming about a food source, milling around a cent...
During the past decade, solving constrained optimization problems with swarm algorithms has received considerable attention among researchers and practitioners. In this chapter, a novel swarm algorithm called the Social Spider Optimization (SSO-C) is presented for solving constrained optimization tasks. The SSO-C algorithm is based on the simulatio...
In this paper, a new method for robustly estimating multiple view relations from point correspondences is presented. The approach combines the popular random sampling consensus (RANSAC) algorithm and the evolutionary method harmony search (HS). With this combination, the proposed method adopts a different sampling strategy than RANSAC to generate p...
Classical image processing methods often face great difficulties while dealing with images containing noise and distortions. Under such conditions, the use of soft computing approaches has been recently extended to address challenging real-world image processing problems. The automatic detection of Leukocytes or White Blood Cells (WBC) still remain...
Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper prese...
The automatic detection of white blood cells (WBCs) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine and computer vision alike. Since WBC can be approximated by an ellipsoid form, an ellipse detector algorithm may be successfully applied in order to recognize such elem...
In Mexico during 2008, were reported 127,604 new cancer cases, 6,347 of them were colorectal cancer cases and 4,276 non-Hodgkin lymphoma (NHL) cases.
To evaluate health related quality of life in non-Hodgkin lymphoma and colorectal cancer cases in different clinical stages, attended in a High Specialty Medical facility at the Instituto Mexicano del...
In Mexico cancer is a public health burden. Nowadays the health care systems pay special attention to patient's perception and satisfaction of the health care received. Satisfaction with quality of health care has an impact in the adherence to the treatment.
To evaluate the satisfaction with the quality of health care received at the IMSS in a grou...
IntroductionQuality of Life is the most studied PRO (patient reported outcome) in cancer patients. With early diagnosis and better treatments in breast cancer, this entity has been transformed in a chronic disease with longer survival. The joint effects of diseases and treatment on quality of life are each day more important to consider in survival...
Quality of life is the most studied PRO (patient reported outcome) in cancer patients. With early diagnosis and better treatments in breast cancer, this entity has been transformed in a chronic disease with longer survival. The joint effects of diseases and treatment on quality of life are each day more important to consider in survival patients.
T...