Carlos E. Galván-Tejada
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View article: Non-Glycemic Clinical Data for Type 2 Diabetes Detection in Mexican Adults: A Comparative Analysis of Atherogenic Indices, Statistical Transformations, and Machine Learning Algorithms
Non-Glycemic Clinical Data for Type 2 Diabetes Detection in Mexican Adults: A Comparative Analysis of Atherogenic Indices, Statistical Transformations, and Machine Learning Algorithms Open
Background: Type 2 diabetes (T2D) is a growing public health problem in Mexico. Lipid profile alterations have been shown to appear years before changes in glycemic biomarkers, and some of the latter are limited in availability, especially…
View article: Explainable Deep Learning for Breast Lesion Classification in Digital and Contrast-Enhanced Mammography
Explainable Deep Learning for Breast Lesion Classification in Digital and Contrast-Enhanced Mammography Open
Background: Artificial intelligence (AI) emerges as a powerful tool to assist breast cancer screening; however, its integration into different mammographic modalities remains insufficiently explored. Digital Mammography (DM) is widely acce…
View article: CBIS-DDSM-R: A Curated Radiomic Feature Dataset for Breast Cancer Classification
CBIS-DDSM-R: A Curated Radiomic Feature Dataset for Breast Cancer Classification Open
Early and accurate breast cancer detection is critical for patient outcomes. The Curated Breast Imaging Subset of the Digital Database for Screening Mammography (CBIS-DDSM) has been instrumental for computer-aided diagnosis (CAD) systems. …
View article: Machine learning predictive model to identify metabolic status in Mexican children, using homeostasis model assessment insulin resistance and amylase enzymatic activity
Machine learning predictive model to identify metabolic status in Mexican children, using homeostasis model assessment insulin resistance and amylase enzymatic activity Open
It is concluded that with these variables and RF, it is feasible to have a prediction model that contributes to identifying this type of patients in the prepathogenic period.
View article: Classification of Small Bowel Lesions in Video Capsule Endoscopy Images Using Enhanced Deep Learning Model
Classification of Small Bowel Lesions in Video Capsule Endoscopy Images Using Enhanced Deep Learning Model Open
Video capsule endoscopy (VCE) is a noninvasive procedure for diagnosing small bowel (SB) lesions. During VCE procedures, the miniature camera captures thousands of images, requiring considerable time and effort from healthcare professional…
View article: Assessing ResNeXt and RegNet Models for Diabetic Retinopathy Classification: A Comprehensive Comparative Study
Assessing ResNeXt and RegNet Models for Diabetic Retinopathy Classification: A Comprehensive Comparative Study Open
Background/Objectives: Diabetic retinopathy is a leading cause of vision impairment worldwide, and the development of reliable automated classification systems is crucial for early diagnosis and clinical decision-making. This study present…
View article: Pix2Pix Generative Adversarial Network for Cellular Nuclei and Cytoplasm Segmentation on Pap Smear Images
Pix2Pix Generative Adversarial Network for Cellular Nuclei and Cytoplasm Segmentation on Pap Smear Images Open
In medical imaging for Pap smear tests, accurately identifying regions of interest, such as the nucleus and cytoplasm, remains a critical challenge due to the complex morphology and overlapping structures in cervical cell images. This comp…
View article: Sex-Specific Ensemble Models for Type 2 Diabetes Classification in the Mexican Population
Sex-Specific Ensemble Models for Type 2 Diabetes Classification in the Mexican Population Open
The proposed sex-specific ensemble models represent a clinically valuable approach to personalized T2D diagnosis. By identifying sex-specific predictive features, this work supports the development of precision medicine tools tailored to t…
View article: Convolutional Neural Network for Depression and Schizophrenia Detection
Convolutional Neural Network for Depression and Schizophrenia Detection Open
Background/Objectives: This study presents a Convolutional Neural Network (CNN) approach for detecting depression and schizophrenia using motor activity patterns represented as images. Participants’ motor activity data were captured and tr…
View article: Comparison of Machine Learning Models for Identification of Depressive Patients through Motor Activity
Comparison of Machine Learning Models for Identification of Depressive Patients through Motor Activity Open
The present study aims to evaluate various classification algorithms for data pertaining to subjects diagnosed with depression and non-depressive subjects. To this end, the data obtained from the "depresjon" dataset proposed by Garcia-Ceja…
View article: Synthetic Data Generation for Pediatric Diabetes Research Using GANs and WGANs
Synthetic Data Generation for Pediatric Diabetes Research Using GANs and WGANs Open
Pediatric diabetes research is often constrained by data scarcity, hindering the development of accurate predictive models for clinical applications. This study addresses this limitation by evaluating the effectiveness of Generative Advers…
View article: Evaluating Feature Selection Methods for Accurate Diagnosis of Diabetic Kidney Disease
Evaluating Feature Selection Methods for Accurate Diagnosis of Diabetic Kidney Disease Open
Background/Objectives: The increase in patients with type 2 diabetes, coupled with the development of complications caused by the same disease is an alarming aspect for the health sector. One of the main complications of diabetes is nephro…
View article: Neural Hierarchical Interpolation for Standardized Precipitation Index Forecasting
Neural Hierarchical Interpolation for Standardized Precipitation Index Forecasting Open
In the context of climate change, studying changes in rainfall patterns is a crucial area of research, remarkably so in arid and semi-arid regions due to the susceptibility of human activities to extreme events such as droughts. Employing …
View article: Setting Ranges in Potential Biomarkers for Type 2 Diabetes Mellitus Patients Early Detection By Sex—An Approach with Machine Learning Algorithms
Setting Ranges in Potential Biomarkers for Type 2 Diabetes Mellitus Patients Early Detection By Sex—An Approach with Machine Learning Algorithms Open
Type 2 diabetes mellitus (T2DM) is one of the most common metabolic diseases in the world and poses a significant public health challenge. Early detection and management of this metabolic disorder is crucial to prevent complications and im…
View article: Auto-Machine-Learning Models for Standardized Precipitation Index Prediction in North–Central Mexico
Auto-Machine-Learning Models for Standardized Precipitation Index Prediction in North–Central Mexico Open
Certain impacts of climate change could potentially be linked to alterations in rainfall patterns, including shifts in rainfall intensity or drought occurrences. Hence, predicting droughts can provide valuable assistance in mitigating the …
View article: Annual Daily Irradiance Analysis of Clusters in Mexico by Machine Learning Algorithms
Annual Daily Irradiance Analysis of Clusters in Mexico by Machine Learning Algorithms Open
The assessment of solar resources involves the utilization of physical or satellite models for the determination of solar radiation on the Earth’s surface. However, a critical aspect of model validation necessitates comparisons against gro…
View article: Classification and selection of the main features for the identification of toxicity in<i>Agaricus</i>and<i>Lepiota</i>with machine learning algorithms
Classification and selection of the main features for the identification of toxicity in<i>Agaricus</i>and<i>Lepiota</i>with machine learning algorithms Open
The occurrence of fungi is cosmopolitan, and while some mushroom species are beneficial to human health, others can be toxic and cause illness problems. This study aimed to analyze the organoleptic, ecological, and morphological characteri…
View article: Optimizing Clinical Diabetes Diagnosis through Generative Adversarial Networks: Evaluation and Validation
Optimizing Clinical Diabetes Diagnosis through Generative Adversarial Networks: Evaluation and Validation Open
The escalating prevalence of Type 2 Diabetes (T2D) represents a substantial burden on global healthcare systems, especially in regions such as Mexico. Existing diagnostic techniques, although effective, often require invasive procedures an…
View article: Detection of Pedestrians in Reverse Camera Using Multimodal Convolutional Neural Networks
Detection of Pedestrians in Reverse Camera Using Multimodal Convolutional Neural Networks Open
In recent years, the application of artificial intelligence (AI) in the automotive industry has led to the development of intelligent systems focused on road safety, aiming to improve protection for drivers and pedestrians worldwide to red…
View article: Feature Selection of Motor Activity in Intervals of Time with Genetics Algorithms for Depression Detection
Feature Selection of Motor Activity in Intervals of Time with Genetics Algorithms for Depression Detection Open
It is estimated that depression affects more than 300 million people in worldwide. Unfortunately, the current method of psychiatric evaluation requires a great effort on the part of clinicians to collect complete information. The aim of th…
View article: Diabetes Detection Models in Mexican Patients by Combining Machine Learning Algorithms and Feature Selection Techniques for Clinical and Paraclinical Attributes: A Comparative Evaluation
Diabetes Detection Models in Mexican Patients by Combining Machine Learning Algorithms and Feature Selection Techniques for Clinical and Paraclinical Attributes: A Comparative Evaluation Open
The development of medical diagnostic models to support healthcare professionals has witnessed remarkable growth in recent years. Among the prevalent health conditions affecting the global population, diabetes stands out as a significant c…
View article: Emotional State Detection Using Electroencephalogram Signals: A Genetic Algorithm Approach
Emotional State Detection Using Electroencephalogram Signals: A Genetic Algorithm Approach Open
Emotion recognition based on electroencephalogram signals (EEG) has been analyzed extensively in different applications, most of them using medical-grade equipment in laboratories. The trend in human-centered artificial intelligence applic…
View article: Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network
Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network Open
The lack of helmet use in motorcyclists is one of the main risk factors with severe consequences in traffic accidents. Wearing a certified motorcycle helmet can reduce the risk of head injuries by 69% and fatalities by 42%. At present ther…
View article: Comparative study of convolutional neural network architectures for gastrointestinal lesions classification
Comparative study of convolutional neural network architectures for gastrointestinal lesions classification Open
The gastrointestinal (GI) tract can be affected by different diseases or lesions such as esophagitis, ulcers, hemorrhoids, and polyps, among others. Some of them can be precursors of cancer such as polyps. Endoscopy is the standard procedu…
View article: Peer Review #2 of "Comparative study of convolutional neural network architectures for gastrointestinal lesions classification (v0.1)"
Peer Review #2 of "Comparative study of convolutional neural network architectures for gastrointestinal lesions classification (v0.1)" Open
The gastrointestinal (GI) tract can be affected by different diseases or lesions such as esophagitis, ulcers, hemorrhoids, and polyps, among others.Some of them can be precursors of cancer such as polyps.Endoscopy is the standard procedure…
View article: Artificial neural network models for prediction of standardized precipitation index in central Mexico
Artificial neural network models for prediction of standardized precipitation index in central Mexico Open
Some of the effects of climate change may be related to a change in patterns of rainfall intensity or rainfall scarcity. So, humanity is facing environmental challenges due to an increase in the occurrence of droughts. Forecasting of droug…
View article: Driver Identification Using Statistical Features of Motor Activity and Genetic Algorithms
Driver Identification Using Statistical Features of Motor Activity and Genetic Algorithms Open
Driver identification refers to the process whose primary purpose is identifying the person behind the steering wheel using collected information about the driver him/herself. The constant monitoring of drivers through sensors generates gr…
View article: GIS-Web tool as surveillance system for acute lymphoblastic leukemia and environmental carcinogens for the youth Mexican population
GIS-Web tool as surveillance system for acute lymphoblastic leukemia and environmental carcinogens for the youth Mexican population Open
Lymphoblastic leukemia is the leading cause of cancer in the Mexican population under 18 years old. On a global scale, Mexico has the highest mortality rate for this age group. Despite this, the specific causes of the disease remain uncert…
View article: Breast Cancer Detection Using Automated Segmentation and Genetic Algorithms
Breast Cancer Detection Using Automated Segmentation and Genetic Algorithms Open
Breast cancer is the most common cancer among women worldwide, after lung cancer. However, early detection of breast cancer can help to reduce death rates in breast cancer patients and also prevent cancer from spreading to other parts of t…