Objectives: To evaluate the acceptability and feasibility of an intervention based on mobile health, for the adoption of healthy lifestyles in prehypertensive people living in low-income urban areas in Argentina, Guatemala and Peru.
Materials And Methods: Prehypertensive people aged 30-60 years were recruited for a pilot study. The intervention included two counseling calls made by a nutritionist followed by a weekly customized text message. An internet-based platform offered support for the implementation of the intervention. Using semi-structured interviews, we evaluated the reach and acceptability of the intervention in the participants and ease of use for the nutritionists.
Results: It was possible to contact 43 of the 45 participants (95%). The average number of calls to contact a subject was two, with a range of 1-9 calls. Two participants could not be reached on their cell phone; five did not receive complete exposure to the intervention. Based on semi-structured interviews, the results showed good acceptability for the intervention by the participants. Nutritionists perceived the platform as friendly and easy to use. Barriers to deliver this intervention were related to difficulties in obtaining an adequate cellular signal.
Conclusions: Given the high penetration of mobile phones in developing countries, it is concluded that it is feasible and acceptable to offer a mobile health based intervention oriented towards lifestyle modification in people with prehypertension or high risk of chronic disease intervention.
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IntroductionAsthma attacks are set off by triggers such as pollutants from the environment, respiratory viruses, physical activity and allergens. The aim of this research is to create a machine learning model using data from mobile health technology to predict and appropriately warn a patient to avoid such triggers.MethodsLightweight machine learning models, XGBoost, Random Forest, and LightGBM were trained and tested on cleaned asthma data with a 70-30 train-test split.
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Senior Resident, Department of Forensic Medicine and Toxicology, AIIMS Bilaspur, Himachal Pradesh 174037, INDIA.
Telemedicine technology plays a crucial role in addressing healthcare challenges, particularly in countries like India, by mitigating physician shortages, reducing patient burden and costs, and aiding in disease prevention. The term telemedicine, meaning "healing at a distance," was coined in 1970 [1]. It encompasses the use of electronic, communication, and information technologies to deliver healthcare services remotely.
View Article and Find Full Text PDFSens Diagn
December 2024
Department of Bioengineering, Rice University Houston TX 77030 USA
CRISPR-Cas-based lateral flow assays (LFAs) have emerged as a promising diagnostic tool for ultrasensitive detection of nucleic acids, offering improved speed, simplicity and cost-effectiveness compared to polymerase chain reaction (PCR)-based assays. However, visual interpretation of CRISPR-Cas-based LFA test results is prone to human error, potentially leading to false-positive or false-negative outcomes when analyzing test/control lines. To address this limitation, we have developed two neural network models: one based on a fully convolutional neural network and the other on a lightweight mobile-optimized neural network for automated interpretation of CRISPR-Cas-based LFA test results.
View Article and Find Full Text PDFIntroduction: Visual Inspection with Acetic Acid (VIA) has been adopted for cervical cancer screening in Kenya and other Low-Middle Income Countries despite providing suboptimal results among HIV-infected women. It is mostly performed by nurses in health centers. Innovative ways of improving the performance of VIA in HIV-infected women are desired.
View Article and Find Full Text PDFJACC Adv
December 2024
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Rheumatic heart disease (RHD) is an important public health problem in Africa. Mapping the epidemiology of RHD involves elucidating its geographic distribution, temporal trends, and demographic characteristics. The prevalence of RHD in Africa varies widely, with estimates ranging from 2.
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