AIMC Topic: Mexico
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Comparative study of machine learning methods for COVID-19 transmission forecasting.
Journal of biomedical informatics
Apr 26, 2021
Within the recent pandemic, scientists and clinicians are engaged in seeking new technology to stop or slow down the COVID-19 pandemic. The benefit of machine learning, as an essential aspect of artificial intelligence, on past epidemics offers a new...
Understanding Attitudes to Change to Healthier Hydration Habits: The Case of High Sugar: Low Water Drinkers in Mexico.
Annals of nutrition & metabolism
Mar 26, 2021
Adults consuming sugar-sweetened beverages (SSBs) are at increased risk of becoming overweight/obese and developing lifestyle-related diseases. Furthermore, a low water intake is associated with increased health risks, such as CKD. These issues are e...
Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico.
International journal of environmental research and public health
Feb 23, 2021
Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders, and the most deadly: Cardiovascular diseases. Due to the limited space in the emergency department, it is important to identify when thoracic pain is...
Understanding global changes in fine-mode aerosols during 2008-2017 using statistical methods and deep learning approach.
Environment international
Jan 29, 2021
Despite their extremely small size, fine-mode aerosols have significant impacts on the environment, climate, and human health. However, current understandings of global changes in fine-mode aerosols are limited. In this study, we employed newly devel...
[Long-term efficacy of parathyroidectomy in secondary and tertiary hyperparathyroidism].
Revista medica del Instituto Mexicano del Seguro Social
Dec 30, 2019
BACKGROUND: Secondary and tertiary hyperparathyroidism (SHPT and THPT), are complications of chronic kidney disease (CKD), characterized by high levels of serum parathormone, hyperphosphatemia or hypercalcemia, respectively. If diet and pharmacologic...
Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study.
Computational and mathematical methods in medicine
Dec 19, 2019
Machine learning, one of the core disciplines of artificial intelligence, is an approach whose main emphasis is analytical model building. In other words, machine learning enables an automaton to make its own decisions based on a previous training pr...
Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico.
BMC medical informatics and decision making
Nov 12, 2019
BACKGROUND: The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type 2 diabetes (T2D) patients, by using available observational patient data and machine-learning-based ...
Circulating Levels of Soluble Klotho and Fibroblast Growth Factor 23 in Diabetic Patients and Its Association with Early Nephropathy.
Archives of medical research
Feb 1, 2019
INTRODUCTION: Diabetic nephropathy is a leading cause of chronic kidney disease (CKD). In diabetes, changes in serum levels of both soluble alpha Klotho (sKL) and fibroblast growth factor 23 (FGF-23) have been associated with CKD progression.
Identification of Diabetic Patients through Clinical and Para-Clinical Features in Mexico: An Approach Using Deep Neural Networks.
International journal of environmental research and public health
Jan 29, 2019
Diabetes is a chronic and noncommunicable but preventable disease that is affecting the Mexican population at worrying levels, being the first place in prevalence worldwide. Early diabetes detection has become important to prevent other health condit...
Molecular identification and in vitro antifungal susceptibility of Scedosporium complex isolates from high-human-activity sites in Mexico.
Mycologia
Mar 1, 2018
The genus Scedosporium is a complex of ubiquitous moulds associated with a wide spectrum of clinical entities, with high mortality principally in immunocompromised hosts. Ecology of these microorganisms has been studied performing isolations from env...
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