Max Chacon

Max Chacon
University of Santiago, Chile | USACH · Departamento de Ingeniería Informática

About

79
Publications
8,564
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
571
Citations
Citations since 2017
30 Research Items
381 Citations
2017201820192020202120222023020406080100
2017201820192020202120222023020406080100
2017201820192020202120222023020406080100
2017201820192020202120222023020406080100
Additional affiliations
August 1996 - present
University of Santiago, Chile
Position
  • Professor (Full)

Publications

Publications (79)
Article
Full-text available
Alzheimer’s disease (AD) is one of the most significant health challenges of our time, affecting a growing number of the elderly population. In recent years, the retina has received increased attention as a candidate for AD biomarkers since it appears to manifest the pathological signatures of the disease. Therefore, its electrical activity may hin...
Article
Full-text available
The mechanism of cerebral blood flow autoregulation can be of great importance in diagnosing and controlling a diversity of cerebrovascular pathologies such as vascular dementia, brain injury, and neurodegenerative diseases. To assess it, there are several methods that use changing postures, such as sit-stand or squat-stand maneuvers. However, the...
Preprint
Alzheimer's disease (AD) is one of the most significant health challenges of our time, affecting a growing number of the elderly population. In recent years, the retina has received increased attention as a candidate for AD biomarkers since it appears to manifest the pathological signatures of the disease. Therefore, its electrical activity may hin...
Article
Objective: The capacity of discriminating between normal and impaired dynamic cerebral autoregulation (dCA), based on spontaneous fluctuations in arterial blood pressure (ABP) and cerebral blood flow (CBF), has considerable clinical relevance. This study aimed to quantify the separate contributions of vascular resistance and compliance as paramete...
Article
Objective: There is emerging evidence that analysing the entropy and complexity of biomedical signals can detect underlying changes in physiology which may be reflective of disease pathology. This approach can be used even when only short recordings of biomedical signals are available. This study aimed to determine whether entropy and complexity m...
Article
Music is one of the most sublime stimulus that human beings can experience. Despite being just an acoustic wave that exert little physical action on a subject, it triggers profound changes in emotions and physiological states. This study explores the possibility of detecting subtle changes in cerebral blood flow velocity in response to emotional re...
Article
Background: Alzheimer's disease (AD) is the most prevalent form of dementia worldwide. This neurodegenerative syndrome affects cognition, memory, behavior, and the visual system, particularly the retina. Objective: This work aims to determine whether the 5xFAD mouse, a transgenic model of AD, displays changes in the function of retinal ganglion...
Article
Full-text available
Se propone una metodología para clasificar señales fisiológicas que representan la autorregulación cerebral (AC), utilizando cuantificadores como complejidad estadística y entropía. Los cuales se obtienen a partir de datos de velocidad de flujo sanguíneo cerebral (VFSC) y presión arterial media (PAM) disponibles en dos bases de datos. Los resultado...
Article
Full-text available
Predicting copper price is essential for making decisions that can affect companies and governments dependent on the copper mining industry. Copper prices follow a time series that is nonlinear and non-stationary, and that has periods that change as a result of potential growth, cyclical fluctuation and errors. Sometimes, the trend and cyclical com...
Preprint
Full-text available
Predicting copper price is essential for making decisions that can affect companies and governments dependent on the copper mining industry. Copper prices follow a time series that is non-linear, non-stationary, and which have periods that change as a result of potential growth, cyclical fluctuation and errors. Sometimes the trend and cyclical comp...
Chapter
Nausea is a common set of symptoms related to several underlying physiological causes, usually difficult to identify a priori. Detecting nausea before emesis (vomiting) is particularly important for patients who are still unconscious after surgery, because emesis may cause various life-threatening complications. Electrogastrography (EGG) is the cut...
Article
Full-text available
We tested the influence of blood pressure variability on the reproducibility of dynamic cerebral autoregulation (DCA) estimates. Data were analyzed from the 2nd CARNet bootstrap initiative, where mean arterial blood pressure (MABP), cerebral blood flow velocity (CBFV) and end tidal CO2 were measured twice in 75 healthy subjects. DCA was analyzed by...
Article
Full-text available
Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctua...
Article
Objective: Different methods to calculate dynamic cerebral autoregulation (dCA) parameters are available. However, most of these methods demonstrate poor reproducibility that limit their reliability for clinical use. Inter-centre differences in study protocols, modelling approaches and default parameter settings have all led to a lack of standardi...
Article
Full-text available
The ability to discriminate between normal and impaired dynamic cerebral autoregulation (CA), based on measurements of spontaneous fluctuations in arterial blood pressure (BP) and cerebral blood flow (CBF), has considerable clinical relevance. We studied 45 normal subjects at rest and under hypercapnia induced by breathing a mixture of carbon dioxi...
Data
NAR step responses in hypercapnia. Step responses produced by the Non-linear Autoregressive models selected for each subject in hypercapnia. (CSV)
Data
Support vector machines. Theoretical fundamentals of Support Vector Machines and Regression. (DOCX)
Data
NAR step responses in baseline. Step responses produced by the Non-linear Autoregressive models selected for each subject in baseline. (CSV)
Data
NFIR parameters in baseline. ν-SVR hyper-parameters of the Non-linear Finite Impulse Response models selected for each subject in baseline. (CSV)
Data
NFIR parameters in hypercapnia. ν-SVR hyper-parameters of the Non-linear Finite Impulse Response models selected for each subject in hypercapnia. (CSV)
Data
NAR parameters in baseline. ν-SVR hyper-parameters of the Non-linear Autoregressive models selected for each subject in baseline. (CSV)
Data
Transfer function coefficients. Gain and phase, in the low and very low frequency ranges, for each subject, in baseline and hypercapnia. (CSV)
Data
NFIR step responses in baseline. Step responses produced by the Non-linear Finite Impulse Response models selected for each subject in baseline. (CSV)
Data
NFIR step responses in hypercapnia. Step responses produced by the Non-linear Finite Impulse Response models selected for each subject in hypercapnia. (CSV)
Data
NAR parameters in hypercapnia. ν-SVR hyper-parameters of the Non-linear Autoregressive models selected for each subject in hypercapnia. (CSV)
Chapter
Objective: We analyzed the performance of linear and nonlinear models to assess dynamic cerebral autoregulation (dCA) from spontaneous variations in healthy subjects and compared it with the use of two known maneuvers to abruptly change arterial blood pressure (BP): thigh cuffs and sit-to-stand. Materials and methods: Cerebral blood flow velocit...
Article
Full-text available
The public health system has restricted economic resources. Because of that, it is necessary to know how the resources are being used and if they are properly distributed. Several works have applied classical approaches based in Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) for this purpose. However, if we have hospitals wi...
Article
Automatic pattern recognition applied to seismic signals from volcanoes may assist seismic monitoring by reducing the workload of analysts, allowing them to focus on more challenging activities, such as producing reports, implementing models and understanding volcanic behaviour. In a previous work we proposed a structure for automatic classificatio...
Article
Fabry disease (FD) is an inherited X-linked, rare disease, with an incidence of 1/40000. Lysosomal storage disorder caused by the decrease or abscence of alpha-galactosidasa A Lysosomal, causes accumulation of GL3 (globotriaosylceramide) and other glycosphingolipids in different cells, including vascular endothelium. Some frequent symptons are neur...
Article
Intracranial Pressure measurements are of great importance for the diagnosis, monitoring and treatment of many vascular brain disturbances. The standard measurement of Intracranial Pressure is performed invasively by perforation of the cranial scalp in the presence of a severe injury. Measuring Intracranial Pressure in a noninvasive way is relevant...
Article
Cerebral hemodynamics is greatly altered by severe head injury. The main variables involved in the system are Mean Arterial Pressure and Intracranial Pressure, which are the independent variables (inputs), and Cerebral Blood Flow, which is the dependent variable (output). The relationship between these signals is not completely understood in severe...
Conference Paper
Full-text available
This paper shows a preliminary study to perform a pattern recognition process for seismic events of the Llaima volcano, one of the most active volcanoes in South America. 1622 classified events registered from the Llaima volcano were considered in this study, taken from 2009 to 2011. The events were divided in four classes: TREMOR (TR), LONG-PERIOD...
Article
Full-text available
The classic dynamic autoregulatory index (ARI), proposed by Aaslid and Tiecks, is one of the most widely used methods to assess the efficiency of dynamic cerebral autoregulation. Although this index is often used in clinical research and is also included in some commercial equipment, it exhibits considerable intra-subject variability, and has the t...
Article
This paper proposes a computer-based classifier to automatically identify four seismic events classes of the Llaima volcano, one of the most active volcanoes in the Southern Andes, situated in the Araucanía Region of Chile. A combination of features that provided good recognition performance in our previous papers concerning the Llaima and Villaric...
Conference Paper
The presented work proposes a new approach for anomaly detection. This approach is based on changes in a population of evolving agents under stress. If conditions are appropriate, changes in the population (modeled by the bioindicators) are representative of the alterations to the environment. This approach, based on an ecological view, improves fu...
Article
Short-segment Barrett's esophagus (SSBE) or long-segment Barrett's esophagus (LSBE) is the consequence of chronic gastroesophageal reflux disease (GERD), which is frequently associated with obesity. Obesity is a significant risk factor for the development of GERD symptoms, erosive esophagitis, Barrett's esophagus, and esophageal adenocarcinoma. Mor...
Article
Full-text available
Diagnoses are a valuable source of information for evaluating a health system. However, they are not used extensively by information systems because diagnoses are normally written in natural language. This work empirically evaluates three machine learning methods to automatically assign codes from the International Classification of Diseases (10th...
Article
Full-text available
REsumEn Los diagnósticos médicos son una fuente valiosa de información para evaluar el funcionamiento de un sistema de salud. Sin embargo, su utilización en sistemas de información se ve dificultada porque éstos se encuentran normalmente escritos en lenguaje natural. Este trabajo evalúa empíricamente tres métodos de Aprendizaje Automático para asig...
Conference Paper
Since the appearance of methods based on machine learning, they have been presented as an alternative to classical phenomenological modeling and there are few initiatives that attempt to integrate them. This paper presents a hybrid paradigm called gray box that blends a phenomenological description (differential equation) and a Support Vector Machi...
Conference Paper
The Critical Closing Pressure (CrCP) of the cerebral circulation has been of considerable interest in recent years due to its implications for a better understanding of cerebral haemodynamics, as well as its contribution to improve the interpretation of clinical measurements. In this research, has been used a new method to estimate CrCP and Resista...
Article
Cerebral blood flow (CBF) is normally controlled by myogenic and metabolic mechanisms that can be impaired in different cerebrovascular conditions. Modeling the influences of arterial blood pressure (ABP) and arterial CO(2) (PaCO(2)) on CBF is an essential step to shed light on regulatory mechanisms and extract clinically relevant parameters. Suppo...
Conference Paper
Full-text available
The stationarity is a feature well defined when the phenomena are represented by linear models, but when the phenomenon has a non linear behavior, this feature is not clear. This work introduces a stationarity analysis of cerebral blood flow velocity (CBFV) and arterial blood pressure (ABP) signals at normal conditions and under a 5% CO2 influence....
Article
The paper describes a feature selection process applied to electrogastrogram (EGG) processing. The data set is formed by 42 EGG records from functional dyspeptic (FD) patients and 22 from healthy controls. A wrapper configuration classifier was implemented to discriminate between both classes. The aim of this work is to compare artificial neural ne...
Article
Full-text available
Intracranial Pressure (ICP) measurements are of great importance for the diagnosis, monitoring and treatment of many vascular brain disturbances. The standard measurement of the ICP is performed invasively by the perforation of the cranial scalp in the presence of traumatic brain injury (TBI). Measuring the ICP in a noninvasive way is relevant for...
Article
Full-text available
This paper proposes a method for reducing the number of search nodes involved in the solution of queries arriving to a Web search engine. The method is applied by the query receptionist machine during situations of sudden peaks in query tra c to reduce the load on the search nodes. The experimental evaluation based on actual traces from users of a...
Article
Full-text available
The aim of the present study was to develop a classifier able to discriminate between healthy controls and dyspeptic patients by analysis of their electrogastrograms. Fifty-six electrogastrograms were analyzed, corresponding to 42 dyspeptic patients and 14 healthy controls. The original signals were subsampled, filtered and divided into the pre-, p...
Article
Full-text available
The aim of the present study was to develop a classifier able to discriminate between healthy controls and dyspeptic patients by analysis of their electrogastrograms. Fifty-six electrogastrograms were analyzed, corresponding to 42 dyspeptic patients and 14 healthy controls. The original signals were subsampled, filtered and divided into the pre-, p...
Article
Each volcano has its own unique seismic activity. The aim of this work is to construct a system able to classify seismic signals for the Villarrica volcano, one of the most active volcanoes in South America. Since seismic signals are the result of particular processes inside the volcano's structure, they can be used to forecast volcanic activity. T...
Conference Paper
The performance of SVMs and ANNs as identifiers of time systems is compared with the purpose of analyzing the Cerebral blood flow Autoregulation System, one of the main systems in the field of cerebral hemodynamics. The main variables of this system are Arterial Blood Pressure (ABP) variations and changes in End-tidal pCO2 (EtCO2). In this work we...
Article
Measurement of dynamic cerebral autoregulation (CA), the transient response of cerebral blood flow (CBF) to changes in arterial blood pressure (ABP), has been performed with an index of autoregulation (ARI), related to the parameters of a second-order differential equation model, namely gain (K), damping factor (D) and time constant (T). Limitation...
Article
Full-text available
AlterORF is a searchable database that contains information regarding alternate open reading frames (ORFs) for over 1.5 million genes in 481 prokaryotic genomes. The objective of the database is to provide a platform for improving genome annotation and to serve as an aid for the identification of prokaryotic genes that potentially encode proteins i...
Article
The most widely used index to evaluate the Cerebral Autoregulation System is the autoregulatory index ARI proposed by Aaslid and Tiecks. Although it is often used in clinical research and is also included in some commercial equipment it has a major drawback: it exhibits great variability even when used in the same patient. It also produces many fal...
Conference Paper
In clusters analysis, a problem of great interest is having methods that allow the representation of the topology of input space without the need to know additional information about it. This gives rise to growing competitive neural methods which are capable of determining the structure of the network autonomously during the process of training. Th...
Conference Paper
Full-text available
DNA analysis by microarrays is a powerful tool that allows replication of the RNA of hundreds of thousands of genes at the same time, generating a large amount of data in multidimensional space that must be analyzed using informatics tools. Various clustering techniques have been applied to analyze the microarrays, but they do not offer a systemati...
Conference Paper
Support Vector Machines (SVM) have been applied extensively to classification and regression problems, but there are few solutions proposed for problems involving time-series. To evaluate their potential, a problem of difficult solution in the field of biological signal modeling has been chosen, namely the characterization of the cerebral blood flo...
Conference Paper
The function of the Cerebral Blood Flow Autoregulation (CBFA) system is to maintain a relatively constant flow of blood to the brain, in spite of changes in arterial blood pressure. A model that characterizes this system is of great use in understanding cerebral hemodynamics and would provide a pattern for evaluating different cerebrovascular disea...
Conference Paper
Full-text available
Recent advances in digital processing of biological signals have made it possible to incorporate more extensive signals, generating a large number of features that must be analyzed to carry out the detection, and thereby acting against the performance of the detection methods. This paper introduces a simple feature reduction method based on correla...
Conference Paper
Technology advances in semiautogenous milling have not been accompanied by advances in the operation of these mills, mainly in the estimates of load levels and the power of the mill. This article presents a grey box model that improves estimate of power. The obtained results are satisfactory and demonstrate that both the phenomenological model and...
Preprint
Full-text available
Recent advances in digital processing of biological signals have made it possible to incorporate more extensive signals, generating a large number of features that must be analyzed to carry out the detection, and thereby acting against the performance of the detection methods. This paper introduces a simple feature reduction method based on correla...
Conference Paper
This study presents the application of Bayesian networks (Bn) to explain Neonatal Intensive Care Unit relationships. Information was compiled retrospectively from the medical records at two neonatal intensive care units of 523 neonates (63 deaths). A total of 31 variables were used for the model, eleven to characterize admission conditions and seve...
Article
Full-text available
Generally, the flaw detection in automated visual inspection consists of two steps: a) identification of potential defects using image processing techniques, and b) classification of potential defects into 'defects' and 'regular structures' (false alarms) using a pattern recognition methodology. In the second step, since several features can be ext...
Article
The automatic detection of flaws through non-destructive testing uses pattern recognition methodology with binary classification. In this problem a decision is made about whether or not an initially segmented hypothetical flaw in an image is in fact a flaw. Neural classifiers are one among a number of different classifiers used in the recognition o...
Article
A time lagged recurrent neural network (TLRN) was implemented to model the dynamic relationship between arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) and its performance was compared to classical linear model such as transfer function analysis, Aaslid's dynamic autoregulation model, and the Wiener-Laguerre moving average fil...
Chapter
Full-text available
A fundamental stage in the design of manufacturing systems is the simultaneous formation of machine cells and families of parts. This problem has been addressed using a number of approaches, but genetic algorithms have had the most success. This paper presents an innovative integer genetic algorithm based on a partial definition of solutions togeth...
Conference Paper
Knowing a patient’s risk at the moment of admission to a medical unit is important for both clinical and administrative decision making: it is fundamental to carry out a health technology assessment. In this paper, we propose a non-supervised learning method based on cluster analysis and genetic algorithms to classify patients according to their ad...
Article
The prediction of the length of stay at the moment of hospital admission is of utmost importance. Many studies have used lineal models to predict this variable, but there are inherent limitations to these models. The use of non lineal models has been scarce. To develop a non lineal model to predict length of stay in intensive care units. Retrospect...
Article
Full-text available
The prediction of the length of stay at the moment of hospital admission is of outmost importance. Many studies have used lineal models to predict this variable, but there are inherent limitations to these models. The use of non lineal models has been scarce. Aim: To develop a non lineal model to predict length of stay in intensive care units. Mate...
Article
1 Trabajo financiado por proyecto Fondecyt Nº 1990920. RESUMEN El presente trabajo esta enfocado a la resolución del problema de asignación de turnos de enfermería aplicado a las Clínicas Chilenas, específicamente Clínicas Las Condes. Existen diversos artículos internacionales y algunos nacionales que tratan el tema [1-7], sin embargo todos ellos s...
Article
Full-text available
Introducción. El lenguaje en medicina representa un valioso instrumento de representación y comunicación que puede ser usado en todos los niveles del sistema de salud, afectando a cada uno de estos niveles según su significado. En otras áreas del saber, como ingeniería, es posible cuantificar numéricamente o dimensionar en forma precisa los hechos...
Article
Full-text available
1 Financiado por Proyectos Fondecyt Nº 1990920 y Nº 799028. RESUMEN La Evaluación de la Efectividad de Múltiples Tecnologías de Salud es un problema complejo, para el cual no existen paradigmas adecuados. La aplicación de Redes Neuronales Artificiales (RNA) ha arrojado una luz de solución, pero los problemas de tratamiento causal de las variables h...
Article
Ab stract: The main variables in the evaluation of the cerebral blood flow autoregulation system are: Mean Arterial Blood Pressure (MABP) variations and changes in End-tidal pCO2 (EtCO2). In this work lineal and non-lineal models with Support Vector Machines (SVMs) are presented to determine the influence of EtCO2 on the Cerebral Blood Flow Velocit...

Network