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Big data in healthcare: management, analysis and future prospects

Sabyasachi Dash, Sushil Kumar Shakyawar, Lokesh Sharma, Sandeep KaushikPublished Jun 19, 2019
DOI Publisher
Researcher verdict
Context only
Use as context only
Benchmark evidence
Missing
Not verified yet
Time to first repro
A few days
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Risk flags
1
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Abstract

Domain fit: AI-adjacent · Paper appears method- or tooling-adjacent to AI workflows with partial ecosystem coverage.

‘Big data’ is massive amounts of information that can work wonders. It has become a topic of special interest for the past two decades because of a great potential that is hidden in it. Various public and private sector industries generate, store, and analyze big data with an aim to improve the services they provide. In the healthcare industry, various sources for big data include hospital records, medical records of patients, results of medical examinations, and devices that are a part of internet of things. Biomedical research also generates a significant portion of big data relevant to public healthcare. This data requires proper management and analysis in order to derive meaningful information. Otherwise, seeking solution by analyzing big data quickly becomes comparable to finding a needle in the haystack. There are various challenges associated with each step of handling big data which can only be surpassed by using high-end computing solutions for big data analysis. That is why, to provide relevant solutions for improving public health, healthcare providers are required to be fully equipped with appropriate infrastructure to systematically generate and analyze big data. An efficient management, analysis, and interpretation of big data can change the game by opening new avenues for modern healthcare. That is exactly why various industries, including the healthcare industry, are taking vigorous steps to convert this potential into better services and financial advantages. With a strong integration of biomedical and healthcare data, modern healthcare organizations can possibly revolutionize the medical therapies and personalized medicine.

Results and benchmarks

Freshness tier: cold
‘Big data’ is massive amounts of information that can work wonders.

Implementation

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Implementation evidence summary
Confidence: medium

datasciencemasters/go is the closest maintained adjacent implementation (Matches contextual method/domain keyword: data science). It is not paper-verified; validate algorithm and evaluation setup against the paper before trusting reported metrics. Community adoption signal: 26265 GitHub stars.

Reproduction risks
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Reproduction readiness

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Last checked: Aug 25, 2026

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Hardware requirements

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Repositories and ecosystem

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  • datasciencemasters/go Adjacent · Confidence: Medium · 26,265 stars

    Matches contextual method/domain keyword: data science

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Research context

1,747

Citations

52

References

Tasks

Big data, Health care, Data science, Computer science, Haystack, The Internet, Health Professions, Health Information Management

Methods

None detected

Domains

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