Big data in healthcare: a new frontier in personalized medicine

@article{Alex2017BigDI,
  title={Big data in healthcare: a new frontier in personalized medicine},
  author={Cheryl Ann Alex and Er and Lidong Wang},
  journal={Journal of Translational Medicine and Research},
  year={2017},
  volume={1}
}
The electronic medical record (EMR) generates information on multiple aspects of patient care. Enormous datasets are now available describing patient behaviors, signs and symptoms of diseases, human– derived information, insurance claims data and pharmacy refill records, providers notes, and imaging. Regular database management systems we have seen in the past are not able to handle these huge datasets. To manage the substantial amounts of data collected about any one given patient, providers… 
The Usefulness and Challenges of Big Data in Healthcare
TLDR
In Malaysia, the focus on big data has started and some initiatives have been put in place to share information patient’s medical records and knowledge among general public, private hospitals and clinics.
Big Data in Healthcare
TLDR
Big Data in healthcare is a new concept introduced in healthcare data analytics and management which is basically focusing in improving the drug and disease discovery, personal healthcare record, electronic health record, effective decision in diagnosis and treatment by healthcare practitioners and at most helps in getting desired and positive health outcome.
Big Data in home healthcare: A new frontier in personalized medicine. Medical emergency services and prediction of hypertension risks
TLDR
An in-depth analysis of the Big Data application in the field of medicine is provided, examining the elements of architecture adapted to healthcare needs and implications relative to wearable sensing devices as well as personalised medicine.
Big Data Analytics using in Healthcare Management System
TLDR
Healthcare data, big data in healthcare systems, applications, advantages, issues of Big Data analytics in healthcare sector, is introduced.
Large Dimensional Data Reduction by Various Feature Selection Techniques: A Short Review
TLDR
This paper focuses on various dynamic FST that not only reduces the dimensionality load but also catalyze the data analysis process.
Personalized Diabetes Analysis Using Correlation-Based Incremental Clustering Algorithm
TLDR
This chapter describes the details about incremental clustering approach, Correlation-Based Incremental Clustering Algorithm (CBICA) to create clusters by applying CBICA to the data of a diabetic patients and observing any relationship which indicates the reason behind the increase of the diabetic level over a specific period of time including frequent visits to healthcare facility.
Big data in healthcare: a new frontier in personalized medicine
TLDR
To manage the substantial amounts of data collected about any one given patient, providers have begun to utilize Big Data Analytics as the primary method for handling this copious amount of data.

References

SHOWING 1-10 OF 15 REFERENCES
BIG DATA ANALYTICS IN HEALTHCARE: A SURVEY
TLDR
The background and the various methods of big data Analytics in healthcare are reviewed, various platforms and algorithms for big data analytics are elaborated and discussion on its advantages and challenges are discussed.
Big Data Analytics in Identification, Treatment, and Cost-Reduction of Hypertension
TLDR
Big Data analytical tools, HTN, and the use of Big Data in healthcare and HTN are discussed, which can be a useful tool for managing data and preventing serious comorbidities and mortality.
Big Data Analytics in Healthcare
TLDR
Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed and potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are examined.
The 'big data' revolution in healthcare: Accelerating value and innovation
TLDR
An era of open information in healthcare is now under way, as pharmaceutical companies and other organizations aggregate years of research and development data in electronic databases to bring the industry to the tipping point.
Quantification of Diabetes Comorbidity Risks across Life Using Nation-Wide Big Claims Data
TLDR
A framework allowing for the first time to quantify nation-wide risks and their age- and sex-dependence for each diabetic comorbidity, and whether the association may be consequential or causal, in a sample of almost two million patients is developed.
Internet of things for remote elderly monitoring: a study from user-centered perspective
TLDR
This paper studies the IoT-enabled systems tackling elderly monitoring to categorize the existing approaches from a new perspective and to introduce a hierarchical model for elderly-centered monitoring.
Mild hypertension in people at low risk
TLDR
Over the past century, life insurers, public health organisations, and prospective studies, including the Framingham Heart Study, have established the relation between increased blood pressure and long term morbidity and mortality.
Big data in healthcare: a new frontier in personalized medicine
TLDR
To manage the substantial amounts of data collected about any one given patient, providers have begun to utilize Big Data Analytics as the primary method for handling this copious amount of data.
Big Data for Health
  • V. Persico
  • Medicine
    Encyclopedia of Big Data Technologies
  • 2019
...
...