Big data in healthcare: management, analysis and future prospects
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
‘Big data’ is massive amounts of information that can work wonders.
Benchmark evidence is limited
Evidence graph: 3 refs, 3 links.
Utility signals: depth 50/100, grounding 75/100, status medium.
Implementation
No direct implementation yet
Maintained implementation evidence is not confirmed for this paper yet.
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Time to first repro: a few days
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.
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Reproduction readiness
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Hardware requirements
- Expect multi-day setup/compute for meaningful reproduction based on current guidance.
Validation caveat
Repositories and ecosystem
Closest related implementations
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- datasciencemasters/go Adjacent · Confidence: Medium · 26,265 stars
Matches contextual method/domain keyword: data science
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Hugging Face artifacts
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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
None detected
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