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Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Enabling large-scale biomedical analysis in the cloud.

Ying-Chih Lin¹, Chin-Sheng Yu, Yen-Jen Lin

¹Master's Program in Biomedical Informatics and Biomedical Engineering, Feng Chia University, No. 100 Wenhwa Road, Seatwen, Taichung 40724, Taiwan ; Department of Applied Mathematics, Feng Chia University, No. 100 Wenhwa Road, Seatwen, Taichung 40724, Taiwan.

Biomed Research International

|November 30, 2013

Summary

This summary is machine-generated.

High-throughput instrumentation generates vast biomedical data, posing storage and computing challenges. Cloud computing offers a solution for managing and analyzing this large-scale data, making it usable for research.

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A User-friendly and Powerful R Analysis of Large-scale Datasets

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Area of Science:

Bioinformatics
Computational Biology
Biomedical Informatics

Background:

High-throughput instrumentation has led to exponential growth in biomedical data volume and complexity.
Storing and computing on these massive datasets presents significant technological challenges.

Purpose of the Study:

To introduce data-intensive computing systems relevant to bioinformatics.
To summarize current cloud-based resources available for bioinformatics applications.
To highlight how these advancements can benefit biomedical research.

Main Methods:

Review of data-intensive computing principles.
Survey of existing cloud computing platforms and services for bioinformatics.
Analysis of the utility of cloud resources for large-scale biomedical data.

Main Results:

Data-intensive computing systems are essential for handling large biomedical datasets.
Cloud computing provides scalable storage and high-performance computing capabilities.
Numerous cloud-based resources are available to support bioinformatics workflows.

Conclusions:

Cloud computing offers a viable solution to the challenges of big biomedical data.
The effective use of cloud resources can accelerate biomedical research and data interpretation.
Integrating cloud solutions enhances the usability and meaningfulness of diverse biomedical data.