M. Chacón

发表

Non-linear multivariate modeling of cerebral hemodynamics with autoregressive Support Vector Machines.

R. Panerai, M. Chacón, Claudio Araya, 2011, Medical engineering & physics.

Pattern recognition applied to seismic signals of the Llaima volcano (Chile): An analysis of the events' features

M. Chacón, Millaray Curilem, F. Huenupán, 2014 .

Non-invasive Intracranial Pressure estimation using Support Vector Machine

M. Chacón, Millaray Curilem, C. Puppo, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms

Max Chacón, Gustavo Fuentealba, Gonzalo Acuña, 2009 .

Detection of patients with functional dyspepsia using wavelet transform applied to their electrogastrogram.

M. Chacón, G. Acuña, G. Curilem, 2009, Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas.

Detection of patients with functional dyspepsia using wavelet transform applied to their electrogastrogram.

M. Chacón, G. Acuña, G. Curilem, 2009 .

Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability

Dae C. Shin, J. L. Jara, S. Van Huffel, 2019, Front. Physiol..

Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study

Dae C. Shin, J. L. Jara, S. Van Huffel, 2018, Physiological measurement.

Neural network modelling of dynamic cerebral autoregulation: assessment and comparison with established methods.

R. Panerai, D. Evans, M. Chacón, 2004, Medical engineering & physics.

Copper Price Prediction Using Support Vector Regression Technique

M. Chacón, Gabriel Astudillo, R. Carrasco, 2020, Applied Sciences.

Non-linear models for the detection of impaired cerebral blood flow autoregulation

J. L. Jara, R. Panerai, M. Chacón, 2018, PloS one.

Assessment of dynamic cerebral autoregulation in humans: Is reproducibility dependent on blood pressure variability?

Dae C. Shin, J. L. Jara, S. Van Huffel, 2020, PloS one.

Recognition of Nausea Patterns by Multichannel Electrogastrography

M. Chacón, Millaray Curilem, S. Ulloa, 2020 .

Copper Price Prediction Using Support Vector Regression Technique

M. Chacón, Gabriel Astudillo, R. Carrasco, 2020, Applied Sciences.

Comparison of Two Non-Invasive Methods for Measuring a Blood Pressure Waveform.

M. Chacón, R. Pereira, N. Nuñez, 2002 .

Retinal Ganglion Cells Functional Changes in a Mouse Model of Alzheimer's Disease Are Linked with Neurotransmitter Alterations.

C. Hetz, A. Palacios, M. Escobar, 2021, Journal of Alzheimer's disease : JAD.

A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix

Mario Inostroza-Ponta, Max Chacón, Manuel Villalobos-Cid, 2016, Journal of Medical Systems.

Analysis of the Influence of Systemic and Intracranial Pressure in Patients with Severe Head Injury Using Linear and Non-linear Models

R. Panerai, M. Chacón, J. Jara, 2015 .

Machine Learning Models and Statistical Complexity to Analyze the Effects of Posture on Cerebral Hemodynamics

M. Chacón, J. Landerretche, Hector Rojas-Pescio, 2022, Entropy.

Comparing Models of Spontaneous Variations, Maneuvers and Indexes to Assess Dynamic Cerebral Autoregulation.

M. Chacón, J. Landerretche, J. Jara, 2018, Acta neurochirurgica. Supplement.

A New Model-Free Index of Dynamic Cerebral Blood Flow Autoregulation

R. Panerai, M. Chacón, J. Jara, 2014, PloS one.

Unconstrained parameter estimation for assessment of dynamic cerebral autoregulation

R. Panerai, M. Chacón, R B Panerai, 2008, Physiological measurement.

Patients Classification by Risk Using Cluster Analysis and Genetic Algorithms

Max Chacón, Oreste Luci, M. Chacón, 2003, CIARP.

Using complexity–entropy planes to detect Parkinson’s disease from short segments of haemodynamic signals

V. Haunton, M. Chacón, J. Fernandez-Muñoz, 2021, Physiological measurement.

Comparison of artificial neural networks an support vector machines for feature selection in electrogastrography signal processing

Millaray Curilem, Sebastian Ulloa, Max Chacon, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

Pattern recognition applied to seismic signals of Llaima volcano (Chile): An evaluation of station-dependent classifiers

Néstor Becerra Yoma, Max Chacón, Millaray Curilem, 2016 .

A Simple Feature Reduction Method for the Detection of Long Biological Signals

Max Chacón, Sergio Jara, Carlos Defilippi, 2005, CIARP.

Empirical evaluation of three machine learning method for automatic classification of neoplastic diagnoses Evaluación empírica de tres métodos de aprendizaje automático para clasificar automáticamente diagnósticos de neoplasias

José L. Jara, Max Chacón, Gonzalo Zelaya, 2011 .

Nonlinear Modeling of Dynamic Cerebral Autoregulation Using Recurrent Neural Networks

David H. Evans, Max Chacón, Ronney Panerai, 2005, CIARP.

Modification of the Growing Neural Gas Algorithm for Cluster Analysis

Max Chacón, Fernando Canales, M. Chacón, 2007, CIARP.

Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study

Dae C. Shin, S. Van Huffel, V. Marmarelis, 2018, Physiological measurement.

Feature Analysis for the Classification of Volcanic Seismic Events Using Support Vector Machines

Max Chacón, Millaray Curilem, Fernando Huenupán, 2014, MICAI.