المؤلفون: Sampa, Masuda Begum, Hossain, Md Nazmul, Hoque, Md Rakibul, Islam, Rafiqul, Yokota, Fumihiko, Nishikitani, Mariko, Ahmed, Ashir

المصدر: JMIR Medical Informatics, Vol 8, Iss 10, p e18331 (2020)

مصطلحات موضوعية: Computer applications to medicine. Medical informatics, R858-859.7

الوصف: BackgroundUric acid is associated with noncommunicable diseases such as cardiovascular diseases, chronic kidney disease, coronary artery disease, stroke, diabetes, metabolic syndrome, vascular dementia, and hypertension. Therefore, uric acid is considered to be a risk factor for the development of noncommunicable diseases. Most studies on uric acid have been performed in developed countries, and the application of machine-learning approaches in uric acid prediction in developing countries is rare. Different machine-learning algorithms will work differently on different types of data in various diseases; therefore, a different investigation is needed for different types of data to identify the most accurate algorithms. Specifically, no study has yet focused on the urban corporate population in Bangladesh, despite the high risk of developing noncommunicable diseases for this population. ObjectiveThe aim of this study was to develop a model for predicting blood uric acid values based on basic health checkup test results, dietary information, and sociodemographic characteristics using machine-learning algorithms. The prediction of health checkup test measurements can be very helpful to reduce health management costs. MethodsVarious machine-learning approaches were used in this study because clinical input data are not completely independent and exhibit complex interactions. Conventional statistical models have limitations to consider these complex interactions, whereas machine learning can consider all possible interactions among input data. We used boosted decision tree regression, decision forest regression, Bayesian linear regression, and linear regression to predict personalized blood uric acid based on basic health checkup test results, dietary information, and sociodemographic characteristics. We evaluated the performance of these five widely used machine-learning models using data collected from 271 employees in the Grameen Bank complex of Dhaka, Bangladesh. ResultsThe mean uric acid level was 6.63 mg/dL, indicating a borderline result for the majority of the sample (normal range

وصف الملف: electronic resource

Relation: https://medinform.jmir.org/2020/10/e18331; https://doaj.org/toc/2291-9694

URL الوصول: https://doaj.org/article/8511e8ca44484f6bbfc55f0b46953cbc

المؤلفون: Nohara, Yasunobu, Kai, Eiko, Ghosh, Partha Pratim, Islam, Rafiqul, Ahmed, Ashir, Kuroda, Masahiro, Inoue, Sozo, Hiramatsu, Tatsuo, Kimura, Michio, Shimizu, Shuji, Kobayashi, Kunihisa, Baba, Yukino, Kashima, Hisashi, Tsuda, Koji, Sugiyama, Masashi, Blondel, Mathieu, Ueda, Naonori, Kitsuregawa, Masaru, Nakashima, Naoki

المصدر: Journal of Medical Internet Research, Vol 17, Iss 1, p e2 (2015)

مصطلحات موضوعية: Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270

الوصف: BackgroundThe prevalence of non-communicable diseases is increasing throughout the world, including developing countries. ObjectiveThe intent was to conduct a study of a preventive medical service in a developing country, combining eHealth checkups and teleconsultation as well as assess stratification rules and the short-term effects of intervention. MethodsWe developed an eHealth system that comprises a set of sensor devices in an attaché case, a data transmission system linked to a mobile network, and a data management application. We provided eHealth checkups for the populations of five villages and the employees of five factories/offices in Bangladesh. Individual health condition was automatically categorized into four grades based on international diagnostic standards: green (healthy), yellow (caution), orange (affected), and red (emergent). We provided teleconsultation for orange- and red-grade subjects and we provided teleprescription for these subjects as required. ResultsThe first checkup was provided to 16,741 subjects. After one year, 2361 subjects participated in the second checkup and the systolic blood pressure of these subjects was significantly decreased from an average of 121 mmHg to an average of 116 mmHg (P

وصف الملف: electronic resource

Relation: http://www.jmir.org/2015/1/e2/; https://doaj.org/toc/1438-8871

URL الوصول: https://doaj.org/article/0e99dcb9aeb94c79a01c1ea0f42d4dec

المؤلفون: Kikuchi K; Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan., Islam R; Medical Information Center, Kyushu University Hospital, Fukuoka, Japan., Sato Y; Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan., Nishikitani M; Medical Information Center, Kyushu University Hospital, Fukuoka, Japan., Izukura R; Social Medicine, Department of Basic Medicine, Faculty of Medical Sciences, Kyushu University, Fukuoka, Japan., Jahan N; Grameen Communications, Dhaka, Bangladesh., Yokota F; Institute for Asian and Oceanian Studies, Kyushu University, Fukuoka, Japan., Ikeda S; Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan., Sultana N; Grameen Communications, Dhaka, Bangladesh., Nessa M; Holy Family Red Crescent Medical College & Hospital, Dhaka, Bangladesh., Nasir M; Holy Family Red Crescent Medical College & Hospital, Dhaka, Bangladesh., Ahmed A; Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan., Kato K; Department of Obstetrics and Gynecology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan., Morokuma S; Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan., Nakashima N; Medical Information Center, Kyushu University Hospital, Fukuoka, Japan.

المصدر: JMIR research protocols [JMIR Res Protoc] 2022 Dec 15; Vol. 11 (12), pp. e41586. Date of Electronic Publication: 2022 Dec 15.

نوع المنشور: Journal Article

بيانات الدورية: Publisher: JMIR Publications Country of Publication: Canada NLM ID: 101599504 Publication Model: Electronic Cited Medium: Print ISSN: 1929-0748 (Print) Linking ISSN: 19290748 NLM ISO Abbreviation: JMIR Res Protoc Subsets: PubMed not MEDLINE

مستخلص: Background: Ensuring an appropriate continuum of care in maternal, newborn, and child health, as well as providing nutrition care, is challenging in remote areas. To make care accessible for mothers and infants, we developed a telehealth care system called Portable Health Clinic for Maternal, Newborn, and Child Health.
Objective: Our study will examine the telehealth care system's effectiveness in improving women's and infants' care uptake and detecting their health problems.
Methods: A quasi-experimental study will be conducted in rural Bangladesh. Villages will be allocated to the intervention and control areas. Pregnant women (≥16 gestational weeks) will participate together with their infants and will be followed up 1 year after delivery or birth. The intervention will include regular health checkups via the Portable Health Clinic telehealth care system, which is equipped with a series of sensors and an information system that can triage participants' health levels based on the results of their checkups. Women and infants will receive care 4 times during the antenatal period, thrice during the postnatal period, and twice during the motherhood and childhood periods. The outcomes will be participants' health checkup coverage, gestational and neonatal complication rates, complementary feeding rates, and health-seeking behaviors. We will use a multilevel logistic regression and a generalized estimating equation to evaluate the intervention's effectiveness.
Results: Recruitment began in June 2020. As of June 2022, we have consented 295 mothers in the study. Data collection is expected to conclude in June 2024.
Conclusions: Our new trial will show the effectiveness and extent of using a telehealth care system to ensure an appropriate continuum of care in maternal, newborn, and child health (from the antenatal period to the motherhood and childhood periods) and improve women's and infants' health status.
Trial Registration: ISRCTN Registry ISRCTN44966621; https://www.isrctn.com/ISRCTN44966621.
International Registered Report Identifier (irrid): DERR1-10.2196/41586.
(©Kimiyo Kikuchi, Rafiqul Islam, Yoko Sato, Mariko Nishikitani, Rieko Izukura, Nusrat Jahan, Fumihiko Yokota, Subaru Ikeda, Nazneen Sultana, Meherun Nessa, Morshed Nasir, Ashir Ahmed, Kiyoko Kato, Seiichi Morokuma, Naoki Nakashima. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 15.12.2022.)