A5010002157- Artificial Intelligence in Healthcare
- AI in cancer detection
- Digital Mental Health Interventions
- Music and Audio Processing
- Speech and Audio Processing
- Mental Health Research Topics
- Indoor and Outdoor Localization Technologies
- Anomaly Detection Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Context-Aware Activity Recognition Systems
- Autonomous Vehicle Technology and Safety
- Traffic Prediction and Management Techniques
- Dental Health and Care Utilization
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Osteoarthritis Treatment and Mechanisms
- Traditional Chinese Medicine Studies
- Medical Imaging and Analysis
- Oral microbiology and periodontitis research
- Gene expression and cancer classification
- IoT and GPS-based Vehicle Safety Systems
- Brain Tumor Detection and Classification
- Video Surveillance and Tracking Methods
- Colorectal Cancer Screening and Detection
- Dementia and Cognitive Impairment Research
Universidad Autónoma de Zacatecas "Francisco García Salinas"
2015-2024
Consejo Nacional de Humanidades, Ciencias y Tecnologías
2020
Tecnológico de Monterrey
2012-2015
Tomato plants are highly affected by diverse diseases. A timely and accurate diagnosis plays an important role to prevent the quality of crops. Recently, deep learning (DL), specifically convolutional neural networks (CNNs), have achieved extraordinary results in many applications, including classification plant This work focused on fine-tuning based comparison state-of-the-art architectures: AlexNet, GoogleNet, Inception V3, Residual Network (ResNet) 18, ResNet 50. An evaluation was finally...
Among the current challenges of Smart City, traffic management and maintenance are utmost importance. Road surface monitoring is currently performed by humans, but road condition one main indicators quality, it may drastically affect fuel consumption safety both drivers pedestrians. Abnormalities in road, such as manholes potholes, can cause accidents when not identified drivers. Furthermore, human-induced abnormalities, speed bumps, could also accidents. In addition, while said obstacles...
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the disease (COVID-19), a highly contagious infectious that has caused many deaths worldwide. Despite global efforts, it continues to cause great losses, and leaving multiple unknowns we must resolve in order face pandemic more effectively. One of questions arisen recently what happens, after recovering from COVID-19. For this reason, objective study identify risk presenting persistent symptoms recovered This...
Depression is a mental disorder characterized by recurrent sadness and loss of interest in the enjoyment positive aspects life, addition to fatigue, causing inability perform daily activities, which leads quality life. To monitor depression (unipolar bipolar patients), traditional methods rely on reports from patients; nevertheless, bias commonly present them. overcome this problem, Ecological Momentary Assessment (EMA) have been widely used, include data behavior, feelings other types...
Oral health represents an essential component in the quality of life people, being a determinant factor general since it may affect risk suffering other conditions, such as chronic diseases. diseases have become one main public problems, where dental caries is condition that most affects oral worldwide, occurring about 90% global population. This has been considered challenge because its high prevalence, besides but preventable disease which can be caused depending on consumption certain...
Emotion recognition based on electroencephalogram signals (EEG) has been analyzed extensively in different applications, most of them using medical-grade equipment laboratories. The trend human-centered artificial intelligence applications is toward portable sensors with reduced size and improved portability that can be taken to real life scenarios, which requires systems efficiently analyze information time. Currently, there no specific set features or number electrodes defined classify...
Major Depression Disease has been increasing in the last few years, affecting around 7 percent of world population, but nowadays techniques to diagnose it are outdated and inefficient. Motor activity data decade is presented as a better way diagnose, treat monitor patients suffering from this illness, achieved through use machine learning algorithms. Disturbances circadian rhythm mental illness increase effectiveness mining process. In paper, comparison motor night, day full carried out...
According to the United Nations, 70% of world’s population will live in cities by 2050. This growth be reflected demand for better services that should adjusted collective and individual needs population. Governments organizations are working on defining implementing strategies enable them respond these challenges. The main challenges related transport its management, considering transportation as a core issue economy, sustainability, development regions. In this way, Intelligent...
The effects of distracted driving are one the main causes deaths and injuries on U.S. roads. According to National Highway Traffic Safety Administration (NHTSA), among different types distractions, use cellphones is highly related car accidents, commonly known as “texting driving”, with around 481,000 drivers by their while driving, about 3450 people killed 391,000 injured in accidents involving 2016 alone. Therefore, this research, a novel methodology detect using cellphone proposed. For...
Worldwide, motor vehicle accidents are one of the leading causes death, with alcohol-related playing a significant role, particularly in child death. Aiming to aid prevention this type accidents, novel non-invasive method capable detecting presence alcohol inside is presented. The proposed methodology uses series low-cost MQ3 sensors located vehicle, whose signals stored, standardized, time-adjusted, and transformed into 5 s window samples. Statistical features extracted from each sample...
Objective. To identify the main research, development and innovation themes associated with infotainment systems artificial intelligence from 2001 to 2022. In addition, performance impact of these areas knowledge using Scopus database.
 Design/Methodology/Approach. The research is based on a two-phase analysis. First an analysis through evaluating bibliometric indicators. Secondly, science mapping publications identified within SciMAT. combination both phases allows for analyzing...
In this paper, we present the development of an infrastructure-less indoor location system (ILS), which relies on use a microphone, magnetometer and light sensor smartphone, all three are essentially passive sensors, relying signals available practically in any building world, no matter how developed region is. our work, merge information from those sensors to estimate user's environment. A multivariate model is applied find location, evaluate quality resulting terms sensitivity specificity....
This work presents a human activity recognition (HAR) model based on audio features. The use of sound as an information source for HAR models represents challenge because wave analyses generate very large amounts data. However, feature selection techniques may reduce the amount data required to represent signal sample. Some features that were analyzed include Mel-frequency cepstral coefficients (MFCC). Although MFCC are commonly used in voice and instrument recognition, their utility within...
Some of the effects climate change may be related to a in patterns rainfall intensity or scarcity. Therefore, humanity is facing environmental challenges due an increase occurrence and droughts. The forecast droughts can great help when trying reduce adverse that scarcity water brings, particularly agriculture. When evaluating conditions scarcity, as well identification characterization droughts, use predictive models drought indices could very useful tool. In this research, utility...
In the area of recognition and classification children activities, numerous works have been proposed that make use different data sources. most them, sensors embedded in children’s garments are used. this work, environmental sound is to generate a activities model through automatic learning techniques, optimized for application on mobile devices. Initially, genetic algorithm feature selection presented, reducing original size dataset used, an important aspect when working with limited...
Depression is a common illness worldwide, affecting an estimated 3.8% of the population, including 5% all adults, in particular, 5.7% adults over 60 years age. Unfortunately, at present, ways to evaluate different mental disorders, like Montgomery-Åsberg depression rating scale (MADRS) and observations, need great effort, on part specialists due lack availability patients obtain necessary information know their conditions detect such as objective way. Based data analysis artificial...
Alzheimer’s disease (AD) is a neurodegenerative that mainly affects older adults. Currently, AD associated with certain hypometabolic biomarkers, beta-amyloid peptides, hyperphosphorylated tau protein, and changes in brain morphology. Accurate diagnosis of AD, as well mild cognitive impairment (MCI) (prodromal stage AD), essential for early care the disease. As result, machine learning techniques have been used recent years AD. In this research, we propose novel methodology to generate...
Type 2 diabetes mellitus (T2DM) represents one of the biggest health problems in Mexico, and it is extremely important to early detect this disease its complications. For a noninvasive detection T2DM, machine learning (ML) approach that uses ensemble classification models with dichotomous output also fast effective for prediction T2D can be used. In article, an technique by hard voting designed implemented using generalized linear regression (GLM), support vector machines (SVM) artificial...
Depression is a mental disorder which typically includes recurrent sadness and loss of interest in the enjoyment positive aspects life, severe cases fatigue, causing inability to perform daily activities, leading progressive quality life. Monitoring depression (unipolar bipolar patients) stats relays on traditional method reports from patients; however, bias commonly present, given patients’ interpretation experiences. Nevertheless, overcome this problem, Ecological Momentary Assessment...
Early diagnoses of Alzheimer's disease (AD) would confer many benefits. Several biomarkers have been proposed to achieve such a task, where features extracted from magnetic resonance imaging (MRI) played an important role. However, studies focused exclusively on morphological characteristics. This study aims determine whether relating the signal and texture image could predict mild cognitive impairment (MCI) AD progression. Clinical, biological, positron emission tomography information MRI...
The prevalence of diabetes mellitus is increasing worldwide, causing health and economic implications. One the principal microvascular complications type 2 Distal Symmetric Polyneuropathy (DSPN), affecting 42.6% population in Mexico. Therefore, purpose this study was to find out predictors complication. dataset contained a total number 140 subjects, including clinical paraclinical features. A multivariate analysis constructed using Boruta as feature selection method Random Forest...