Empowering the Healthcare Worker Using the Portable Health Clinic

Kai, Eiko; Rebeiro‐Hargrave, Andrew; Inoue, Sozo; Nohara, Yasunobu; Maruf, Rafiqul Islam; Nakashima, Naoki; Ahmed, Ashir

doi:10.1109/aina.2014.108

Cited by 10 publications

(3 citation statements)

References 5 publications

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“…Reducing the workload of doctors reduces the cost of the medical program. We are currently analyzing eHealth records using the association rule to support the clinical decisions of medical staff [19]. This analysis can help doctors to add prescription data into the system faster because the system predicts what the doctors want to do and can show candidate inputs and instructions.…”

Section: Discussionmentioning

confidence: 99%

Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries: Verification Study

Nohara¹,

Kai²,

Ghosh³

et al. 2015

J Med Internet Res

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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<.001). Based on these results, we propose a cost-effective method using a machine learning technique (random forest method) using the medical interview, subject profiles, and checkup results as predictor to avoid costly measurements of blood sugar, to ensure sustainability of the program in developing countries.ConclusionsThe results of this study demonstrate the benefits of an eHealth checkup and teleconsultation program as an effective health care system in developing countries.

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Section: Discussionmentioning

confidence: 99%

Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries: Verification Study

Nohara¹,

Kai²,

Ghosh³

et al. 2015

J Med Internet Res

Self Cite

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“…Mobile health [65] and network medical treatment [66] can greatly simplify the work of hospital staff and make it more convenient to seek medical advice and more accurate to grasp physical quality.…”

Section: Mobile Health Network Medical Treatment and Personalized Hementioning

confidence: 99%

A Survey of Data Processing of EMR (Electronic Medical Record) Based on Data Mining

Sun¹,

Liu²,

Cai³

et al. 2017

Preprint

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At present, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed and treatment results. EMR has been recognized as a valuable resource for large scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation and data reduction. For semi-structured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (Named Entity Recognition) and RE (Relation Extraction). In this paper, we introduce the process of EMR processing, including data collection, data preprocessing, data mining, evaluation and knowledge application, analyze the current status of the key technologies, such as data preprocessing and data mining, and provide an overview of the application domains and prospects of EMR mining technologies. Finally, we summarize the existing problems in the research of EMR mining, and review the development trends.

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“…Proposed system was a remote healthcare consultancy system. Associate rule technique was applied in order to build proposed system [119].…”

Section: Association Examples In Healthcarementioning

confidence: 99%

Techniques of Data Mining In Healthcare: A Review

Ahmad¹,

Qamar²,

Rizvi³

2015

IJCA

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Data mining is gaining popularity in disparate research fields due to its boundless applications and approaches to mine the data in an appropriate manner. Owing to the changes, the current world acquiring, it is one of the optimal approach for approximating the nearby future consequences. Along with advanced researches in healthcare monstrous of data are available, but the main difficulty is how to cultivate the existing information into a useful practices. To unfold this hurdle the concept of data mining is the best suited. Data mining have a great potential to enable healthcare systems to use data more efficiently and effectively. Hence, it improves care and reduces costs. This paper reviews various Data Mining techniques such as classification, clustering, association, regression in health domain. It also highlights applications, challenges and future work of Data Mining in healthcare.

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Empowering the Healthcare Worker Using the Portable Health Clinic

Cited by 10 publications

References 5 publications

Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries: Verification Study

Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries: Verification Study

A Survey of Data Processing of EMR (Electronic Medical Record) Based on Data Mining

Techniques of Data Mining In Healthcare: A Review

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