A5013945325- Advanced MRI Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Atomic and Subatomic Physics Research
- Biomedical and Engineering Education
- COVID-19 diagnosis using AI
- Lung Cancer Diagnosis and Treatment
- Cardiac pacing and defibrillation studies
- Cardiac Arrhythmias and Treatments
- Problem and Project Based Learning
- MRI in cancer diagnosis
- Machine Learning in Healthcare
- Lanthanide and Transition Metal Complexes
- Alzheimer's disease research and treatments
- Dementia and Cognitive Impairment Research
- Advanced Neuroimaging Techniques and Applications
- Educational Leadership and Innovation
- Vitamin D Research Studies
- Physical Education and Gymnastics
- Cardiovascular Disease and Adiposity
- Sparse and Compressive Sensing Techniques
- Neural Networks and Applications
- Sex and Gender in Healthcare
- Healthcare Regulation
- Innovative Teaching Methods
- Cardiac electrophysiology and arrhythmias
Tecnológico de Monterrey
2015-2024
St. Joseph’s Healthcare Hamilton
2016-2020
McMaster University
2016-2019
Universidad Autónoma Metropolitana
2012
The growing demand for more efficient, timely, and safer health services, together with insufficient resources, put unprecedented pressure on systems worldwide. This challenge has motivated the application of principles tools operations management lean to healthcare processes maximize value while reducing waste. Consequently, there is an increasing need professionals appropriate clinical experience skills in process engineering. Given their multidisciplinary education training, biomedical...
Alzheimer's Disease (AD) is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills. The ability to correctly predict the diagnosis of disease in its earliest stages can help physicians make more informed clinical decisions on therapy plans.This study aimed determine whether unsupervised discovering latent classes subjects with Mild Cognitive Impairment (MCI) may be useful finding different prodromal AD and/or a low MCI conversion risk.Total 18 features...
Biomedical engineering (BME) is one of the fastest-growing fields worldwide. BME professionals are extensively employed in health technology and healthcare industries. Hence, their education must prepare them to face challenge a rapidly evolving technological environment. signals systems analysis essential undergraduate education. Unfortunately, students often underestimate importance courses as they do not perceive these courses’ practical applications future professional practice. In this...
Abstract Background Bioinstrumentation is essential to biomedical engineering (BME) undergraduate education and professional practice. Several strategies have been suggested provide BME students with hands-on experiences throughout the curriculum, promoting their preparedness pursue careers in industry academia while increasing learning engagement. This paper describes implementation of challenge-based (CBL) an bioinstrumentation blended course over COVID-19 pandemic. Methods The CBL...
Purpose Dynamic phosphorus MR spectroscopic imaging ( 31 P‐MRSI) experiments require temporal resolution on the order of seconds to concurrently assess different muscle groups. A highly accelerated pulse sequence combining flyback echo‐planar (EPSI) and compressed sensing was developed tested in a phantom healthy humans during an exercise‐recovery challenge lower leg muscles, using clinical 3T MRI. Methods EPSI readout designed achieve 2.25 × cm 2 over 18 field view (i.e., 8 matrix) combined...
A two-step method for obtaining a volumetric estimation of COVID-19 related lesion from CT images is proposed. The first step consists in applying U-NET convolutional neural network to provide segmentation the lung-parenchyma. This architecture trained and validated using Thoracic Volume Pleural Effusion Segmentations Diseased Lungs Benchmarking Chest Processing Pipelines (PleThora) dataset, which publicly available. second an automatic algorithm based on probabilistic active contour (PACO)...
Cardiac resynchronization therapy (CRT) improves functional classification among patients with left ventricle malfunction and ventricular electric conduction disorders. However, a high percentage of subjects under CRT (20%-30%) do not show any improvement. Nonetheless the presence mechanical contraction dyssynchrony in ventricles has been proposed as an indicator response. This work proposes automated model severity dyssynchrony. The includes clinical data such ejection fraction (LVEF), QRS...
ABSTRACT Background Alzheimer’s disease (AD) is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills. The ability to correctly predict the diagnosis of in its earliest stages can help physicians make more informed clinical decisions on therapy plans. Objective To determine whether unsupervised discovering latent classes subjects with mild cognitive impairment (MCI) may be useful finding different prodromal AD and/or have a low MCI conversion risk....
Diffusion weighted imaging is a widely used technique for the assessment of white matter using tractography. Nevertheless, due to practical constraints such as limited acquisition times, differences in scanning methods and physical artifacts, these images must be processed by image correction algorithms order produce reliable results. State-of-the art susceptibility FSL's TOPUP algorithm typically requires at least two acquired with no diffusion encoding (b=0) regular reverse phase...
Biomedical engineering undergraduate students often underestimate the relevance of their courses as they hardly perceive practical application in future professional development, resulting a lack interest, motivation, and engagement. This issue may be addressed by implementing or "hands-on" learning experiences that allow to construct knowledge apply skills real-world scenarios. work proposes create supported blended spaces, including traditional classrooms for direct instruction, daily-life...
Introduction: Mild behavioral impairment (MBI), and particularly its impulse dyscontrol domain, has been linked to brain alterations suggestive of Alzheimer’s disease (AD) in subjects without dementia. We aimed analyze the association with loss integrity white-matter tracts a group cognitively normal older adults. Materials Methods: Using linear regression models, we analyzed effect scores (using MBI-Checklist, MBI-C) on diffusivity metrics (fractional anisotropy, FA; mean diffusivity)...
Evidence supports that the virus SARS-CoV-2 has a potential neuroinvasion causing neurological symptoms, even after recovery. Diffusion Weighted Imaging (DWI) allows us to detect microstructural changes in white matter tissue integrity. In this work, we studied manifestations of COVID-19 apparent diffusion coeficient (ADC), fractional anisotropy (FA), and metrics derived from fixel-based analysis (FBA) such as fiber density (FD), cross-section (FC), (FDC). We found statistically significant...
Quantifying the affected lung areas in a COVID-19 patient is important to assess disease progression and treatment response. It also helps with phenotype differentiation prognosis prediction. In clinical setting, this quantification performed manually by an expert radiologist, based on their experience knowledge, however it time-consuming task inter-observer variability, creating thus need develop automatic algorithms delimitate diseased areas. Convolutional neural networks (CNNs) have been...
Purpose: A semiautomatic two-step methodology is proposed to obtain a volumetric estimation of the COVID-19 related lesions on CT images.Methods: The first step consists lesion segmentation using non-supervised approach based probabilistic active contours, making it interesting because does not need large dataset train model. second uses CNN segment lung parenchyma and then whole-lung volume estimation. Finally, resultant masks are used compute percentage in lungs. validated publicly...
Introduction: The cognitive effects of cross-sex hormone therapy (CSHT) are not well understood. In cisgender individuals, sex can impact neurotransmitter levels and structural anatomy. Similarly, in gender-diverse persons, CSHT has been associated with neural adaptations, such as growth brain structures resembling those observed individuals the same sex. Hormone-related changes learning memory, seen menopause, physiological hypogonadism or a decline hormones, estradiol. present study...