A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study

Autor: Masuda Begum Sampa, Topu Biswas, Md Siddikur Rahman, Nor Hidayati Binti Abdul Aziz, Md Nazmul Hossain, Nor Azlina Ab Aziz

Publikováno v: JMIR Diabetes, Vol 8, p e49113 (2023)

BackgroundOver the past few decades, diabetes has become a serious public health concern worldwide, particularly in Bangladesh. The advancement of artificial intelligence can be reaped in the prediction of blood glucose levels for better health manag

Externí odkaz: https://doaj.org/article/91c8dcce9b8e48cfa290f979f303b065

A Machine Learning Model Based Web App to Predict Diabetic Blood Glucose

Autor: Masuda Begum Sampa, Topu Biswas, M Rakibul Hoque, M Nazmul Hossain, Ashir Ahmed

Aim of this study is to use machine learning approaches for predicting blood glucose based on basic non-invasive health checkup test results, dietary information, and socio-demographic characteristics and to develop a web application to predict blood

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::636e96d28e7b358cd36c320c35b576bf
https://doi.org/10.21203/rs.3.rs-2488325/v1

Influence of Factors on the Adoption and Use of ICT-Based eHealth Technology by Urban Corporate People

Autor: Md. Rakibul Hoque, Akira Fukuda, Fumihiko Yokota, Rafiqul Islam, Masuda Begum Sampa, Md. Nazmul Hossain, Ashir Ahmed, Mariko Nishikitani

Publikováno v: Journal of Service Science and Management. 13:1-19

The aim of this study is to investigate the influence of the factors that affect the use of a PHC system (portable health clinic, an eHealth technology) by urban corporate people in Bangladesh. This study uses the first and second versions of the tec

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0cce84799cf7480e60bb9769250abfc2
https://doi.org/10.4236/jssm.2020.131001

A Data Enhancement Approach to Improve Machine Learning Performance for Predicting Health Status Using Remote Healthcare Data

Autor: Ashir Ahmed, Shaira Tabassum, Rafiqul Islam, Fumihiko Yokota, Masuda Begum Sampa, Naoki Nakashima

Publikováno v: 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT).

Machine Learning (ML) is becoming tremendously important to improve the performance of remote healthcare systems. Portable health clinic (PHC), a remote healthcare system contains a triage function that classifies the patients in two major groups - (

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::32b8e1daa4b2852bd62496e7f0a88d3a
https://doi.org/10.1109/icaict51780.2020.9333506

Redesigning Portable Health Clinic Platform as a Remote Healthcare System to Tackle COVID-19 Pandemic Situation in Unreached Communities

Autor: Masuda Begum Sampa, Kimiyo Kikuchi, Moshiur Rahman, Naoki Nakashima, Ashir Ahmed, Faiz Shah, Rafiqul Islam, Fumihiko Yokota, Mariko Nishikitani, Rakibul Hoque

Publikováno v: International Journal of Environmental Research and Public Health
Volume 17
Issue 13
International Journal of Environmental Research and Public Health, Vol 17, Iss 4709, p 4709 (2020)

Medical staff carry an inordinate risk of infection from patients, and many doctors, nurses, and other healthcare workers are affected by COVID-19 worldwide. The unreached communities with noncommunicable diseases (NCDs) such as chronic cardiovascula

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6556510638cc70757b720bc6487f910