Data mining techniques in Indian healthcare: A short review

Das, Amit Kumar; Kedia, Aman; Sinha, Lisha; Goswami, Saptarsi; Chakrabarti, Tamal; Chakrabarti, Amlan

doi:10.1109/mami.2015.7456611

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…A compreensão destes conceitos é de suma importância visto o enorme volume de dados a serem lidos e/ou escritos. Assim, a mineração de dados em séries temporais possui inúmeras aplicações diretas dentro da indústria, análise de dados bancários, análise de fraudes, mineração de bio-dados, análise de dados de assistência médica etc., auxiliando na tomada de decisão [4] [6].…”

Section: Resultsunclassified

Mineração De Dados Aplicada À Séries Temporais Resultantes De Sinais Motores Da Doença De Parkinson

Folador¹,

Andrade²

2018

Anais Do v Congresso Brasileiro De Eletromiografia E Cinesiologia E X Simpósio De Engenharia Biomédica

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Resumo: Nos últimos anos, a quantidade de dados gerados na área da saúde tem aumentado consideravelmente. Neste sentido, é necessário extrair informações destes dados, a fim de auxiliar na tomada de decisão. O trabalho aqui proposto consiste na revisão do estado atual da literatura e identificação de técnicas de mineração de dados que têm sido utilizadas na extração de informações de séries temporais, e que resultem do registro de sinais na área da engenharia biomédica e sinais motores da doença de Parkinson. Os resultados da revisão sugerem que os métodos mais utilizados na mineração de dados representados por séries temporais são: Árvore

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Section: Resultsunclassified

Mineração De Dados Aplicada À Séries Temporais Resultantes De Sinais Motores Da Doença De Parkinson

Folador¹,

Andrade²

2018

Anais Do v Congresso Brasileiro De Eletromiografia E Cinesiologia E X Simpósio De Engenharia Biomédica

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“…The main three types of data [29] are structured, unstructured, and semi-structured data. Table 5 presents the details of these data types.…”

Section: Types Of Healthcare Datamentioning

confidence: 99%

A Comprehensive Survey on Data Utility and Privacy: Taking Indian Healthcare System as a Potential Case Study

2021

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Background: According to the renowned and Oscar award-winning American actor and film director Marlon Brando, “privacy is not something that I am merely entitled to, it is an absolute prerequisite.” Privacy threats and data breaches occur daily, and countries are mitigating the consequences caused by privacy and data breaches. The Indian healthcare industry is one of the largest and rapidly developing industry. Overall, healthcare management is changing from disease-centric into patient-centric systems. Healthcare data analysis also plays a crucial role in healthcare management, and the privacy of patient records must receive equal attention. Purpose: This paper mainly presents the utility and privacy factors of the Indian healthcare data and discusses the utility aspect and privacy problems concerning Indian healthcare systems. It defines policies that reform Indian healthcare systems. The case study of the NITI Aayog report is presented to explain how reformation occurs in Indian healthcare systems. Findings: It is found that there have been numerous research studies conducted on Indian healthcare data across all dimensions; however, privacy problems in healthcare, specifically in India, are caused by prevalent complacency, culture, politics, budget limitations, large population, and existing infrastructures. This paper reviews the Indian healthcare system and the applications that drive it. Additionally, the paper also maps that how privacy issues are happening in every healthcare sector in India. Originality/Value: To understand these factors and gain insights, understanding Indian healthcare systems first is crucial. To the best of our knowledge, we found no recent papers that thoroughly reviewed the Indian healthcare system and its privacy issues. The paper is original in terms of its overview of the healthcare system and privacy issues. Social Implications: Privacy has been the most ignored part of the Indian healthcare system. With India being a country with a population of 130 billion, much healthcare data are generated every day. The chances of data breaches and other privacy violations on such sensitive data cannot be avoided as they cause severe concerns for individuals. This paper segregates the healthcare system’s advances and lists the privacy that needs to be addressed first.

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Knowledge discovery, analysis and prediction in healthcare using data mining and analytics

Raul¹,

Patil²,

Raheja³

et al. 2016

2016 2nd International Conference on Next Generation Computing Technologies (NGCT)

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Data mining techniques in Indian healthcare: A short review

Cited by 4 publications

References 32 publications

Mineração De Dados Aplicada À Séries Temporais Resultantes De Sinais Motores Da Doença De Parkinson

Mineração De Dados Aplicada À Séries Temporais Resultantes De Sinais Motores Da Doença De Parkinson

A Comprehensive Survey on Data Utility and Privacy: Taking Indian Healthcare System as a Potential Case Study

Knowledge discovery, analysis and prediction in healthcare using data mining and analytics

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