ICT framework for collaborative healthcare services: A case study of Cleft Lip/Palate treatment network in northern Thailand

Choosri, Noppon; Khwanngem, Krit; Yu, Hongnian; Thongbunjob, Krid; Sukhahuta, Rattasit; Natwichai, Juggapong; Boonma, Pruet

doi:10.1109/skima.2016.7916204

Cited by 1 publication

(1 citation statement)

References 15 publications

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“…[12] There are different domains of healthcare where big data analytics play a pivot role. Some examples are such as in predicting heart attack and providing medical treatment according to the individual [13], prediction of heart disease [14], prediction of patients with heart failure [15], framework for cardiovascular diseases [16], Chronic Obstructive Pulmonary Disease (COPD) diagnosis in individual patient [17], Cleft-Lip/Palate treatment [18], diabetes management applications [19] etc. Among different health care domains cancer diagnosis and treatment is a major challenge where cancer is major reason for death of millions of people every year.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Big Data Analytics Based Framework for Premature Recognition of Breast Cancer

Venkatesan*,

Kulkarni,

Menon

et al. 2020

IJITEE

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Healthcare industry is fast growing and expanding in rapid pace. The volume and veracity of data generated in the industry is massive and requires huge storages and handling capability. Big data is empowered with such robust abilities and hence most suitable for handing large amount of data. Further, hese data could be utilized towards building predictive and forecasting models. Breast cancer is a deadly form of cancer majorly affecting women around the globe. The concept of big data and predictive analytics is being explored in the paper towards early diagnosis of breast cancer. This paper surveys various literatures available on application of big data analysis for breast cancer. Subsequently a comprehensive framework is being proposed based on the gaps identified. Different machine learning algorithms which can be applied in the framework is also detailed in the paper. Such frameworks when implemented will greatly help in handling the massive data available and aid in early detection of breast cancer.

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Section: Introductionmentioning

confidence: 99%