Table 1.
Characteristics of existing review/conceptual studies on the related topics.
Paper | Scope | Timeframe Considered | Number of Papers Reviewed |
---|---|---|---|
[11] | Awareness effect in type 2 diabetes | 2001–2005 | 18 |
[12] | Fraud detection | N/A | N/A |
[13] | Data mining techniques and guidelines for clinical medicine | N/A | N/A |
[14] | Text mining, Ontologies | N/A | N/A |
[15] | Challenges and future direction | N/A | N/A |
[16] | Data mining algorithm, their performance in clinical medicine | 1998–2008 | 84 |
[17] | Clinical medicine | N/A | N/A |
[18] | Skin diseases | N/A | N/A |
[19] | Clinical medicine | N/A | 84 |
[20] | Algorithms, and guideline | N/A | N/A |
[9] | Data mining process and algorithms | N/A | N/A |
[21] | Algorithms for locally frequent disease in healthcare administration, clinical care and research, and training | N/A | N/A |
[7] | Electronic Medical Record (EMR) and Visual analytics | N/A | N/A |
[10] | Big data, Level of data usage | N/A | N/A |
[22] | MapReduce architectural framework based big data analytics | 2007–2014 | 32 |
[23] | Big data analytics and its opportunities | N/A | N/A |
[24] | Big data analytics in image processing, signal processing, and genomics | N/A | N/A |
[25] | Social media data mining to detect Adverse Drug Reaction, Natural language processing techniques (NLP) | 2004–2014 | 39 |
[26] | Text mining, Adverse Drug Reaction detection | N/A | N/A |
[8] | Big data analytics in critical care | N/A | N/A |
[27] | Methodology of big data analytics in healthcare | N/A | N/A |
Our study | Application and theoretical perspective of data mining and big data analytics in whole healthcare domain | 2005–2016 | 117 |
N/A represents Not Reported.