Cite this DOI

Shweta S.Kaddi, & Malini M.Patil (2020). Challenges and Trends in Clinical Data Analytics. *Journal of Science & Technology*, 348–360. https://doi.org/10.46243/jst.2020.v5.i4.pp348-360

@article{shwetaskaddi2020challenges,
  author    = {Shweta S.Kaddi and Malini M.Patil},
  title     = {{Challenges and Trends in Clinical Data Analytics}},
  journal   = {Journal of Science \& Technology},
  year      = {2020},
  month     = {jul},
  number    = {Volume 5},
  pages     = {348--360},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2020.v5.i4.pp348-360},
  url       = {https://doi.org/10.46243/jst.2020.v5.i4.pp348-360},
  language  = {en},
  abstract  = {:Today’s technological advancements facilitated the researcher in collecting and organizing various forms of healthcare data. Data is an integral part of health care analytics. Drug discovery for clinical data analytics forms an important breakthrough work in terms of computational approaches in health care systems. On the other hand, healthcare analysis provides better value for money. The health care data management is very challenging as 80\% of the data is unstructured as it includes handwritten documents, images; computer-generated clinical reports such as MRI, ECG, city scan, etc. The paper aims at providing a summary of work carried out by scientists and researchers who worked in health care domains. More precisely the work focuses on clinical data analysis for the period 2013 to 2019. The organization of the work carried out is specifically with concerned to data sets, Techniques, and Methods used, Tools adopted, Key Findings in clinical data analysis. The overall objective is to identify the current challenges, trends, and gaps in clinical data analysis. The pathway of the work is focused on carrying out on the bibliometric survey and summarization of the key findings in a novel way.}
}

TY  - JOUR
TI  - Challenges and Trends in Clinical Data Analytics
AU  - Shweta S.Kaddi
AU  - Malini M.Patil
JO  - Journal of Science & Technology
PY  - 2020
DA  - 2020/07/30/
IS  - Volume 5
SP  - 348
EP  - 360
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - :Today’s technological advancements facilitated the researcher in collecting and organizing various forms of healthcare data. Data is an integral part of health care analytics. Drug discovery for clinical data analytics forms an important breakthrough work in terms of computational approaches in health care systems. On the other hand, healthcare analysis provides better value for money. The health care data management is very challenging as 80% of the data is unstructured as it includes handwritten documents, images; computer-generated clinical reports such as MRI, ECG, city scan, etc. The paper aims at providing a summary of work carried out by scientists and researchers who worked in health care domains. More precisely the work focuses on clinical data analysis for the period 2013 to 2019. The organization of the work carried out is specifically with concerned to data sets, Techniques, and Methods used, Tools adopted, Key Findings in clinical data analysis. The overall objective is to identify the current challenges, trends, and gaps in clinical data analysis. The pathway of the work is focused on carrying out on the bibliometric survey and summarization of the key findings in a novel way.
DO  - 10.46243/jst.2020.v5.i4.pp348-360
UR  - https://doi.org/10.46243/jst.2020.v5.i4.pp348-360
ER  -

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    "URL": "https://doi.org/10.46243/jst.2020.v5.i4.pp348-360",
    "title": "Challenges and Trends in Clinical Data Analytics",
    "source": "Smart Scholars DOI Registry",
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    "author": [
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            "family": "Shweta S.Kaddi",
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    "language": "en",
    "abstract": ":Today’s technological advancements facilitated the researcher in collecting and organizing various forms of healthcare data. Data is an integral part of health care analytics. Drug discovery for clinical data analytics forms an important breakthrough work in terms of computational approaches in health care systems. On the other hand, healthcare analysis provides better value for money. The health care data management is very challenging as 80% of the data is unstructured as it includes handwritten documents, images; computer-generated clinical reports such as MRI, ECG, city scan, etc. The paper aims at providing a summary of work carried out by scientists and researchers who worked in health care domains. More precisely the work focuses on clinical data analysis for the period 2013 to 2019. The organization of the work carried out is specifically with concerned to data sets, Techniques, and Methods used, Tools adopted, Key Findings in clinical data analysis. The overall objective is to identify the current challenges, trends, and gaps in clinical data analysis. The pathway of the work is focused on carrying out on the bibliometric survey and summarization of the key findings in a novel way.",
    "ISSN": "2456-5660"
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From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2020.v5.i4.pp348-360 gives all four in one JSON answer.