Managing uncertainty in imputing missing symptom value for healthcare of rural India

Purpose In India, 67% of the total population live in remote area, where providing primary healthcare is a real challenge due to the scarcity of doctors. Health kiosks are deployed in remote villages and basic health data like blood pressure, pulse rate, height–weight, BMI, Oxygen saturation level (...

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Vydané v:	Health information science and systems Ročník 7; číslo 1; s. 5 - 15
Hlavní autori:	Das, Sayan, Sil, Jaya
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 18.02.2019 BioMed Central Ltd Springer Nature B.V
Predmet:	Algorithms Analysis Bioinformatics Blood pressure Body mass index Clustering Computational Biology/Bioinformatics Computer Science Computer simulation Cost function Data acquisition Datasets Error analysis Fuzzy sets Ground truth Health care Health Informatics Heart rate Information Systems and Communication Service Kiosks Monte Carlo methods Monte Carlo simulation Novels Oxygen content Patients Physicians Primary health care Regression models Shortages Signs and symptoms Special Issue on Application of Artificial Intelligence in Health Research Uncertainty India Softmax classifier Monte Carlo method Fuzzification Missing value Regression model Rural healthcare
ISSN:	2047-2501, 2047-2501
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