Sensor, signal, and imaging informatics: big data and smart health technologies.

Area of Science:

• Medical Informatics
• Sensor, Signal, and Imaging Informatics

Background:

• Innovative sensors are increasingly used to enrich large datasets.
• These Big Data collections capture extensive study population variability.
• Traditional data processing tools are inadequate for current Big Data challenges.

Purpose of the Study:

• To present a curated selection of research in Sensor, Signal, and Imaging Informatics from 2013.
• To highlight advancements focusing on Big Data and Smart Health Technologies.

Main Methods:

• Systematic literature search of PubMed and Web of Science databases.
• Double-blind peer review process for paper selection.
• Utilized MeSH keywords provided by domain experts.

Main Results:

• Big Data presents significant challenges in capture, storage, search, sharing, transfer, and exploitation.
• Emerging sensors contribute to the growing volume and complexity of health data.
• Existing processing tools are not adapted to handle the scale and complexity of Big Data.

Conclusions:

• Development of novel tools specifically designed for Big Data is essential.
• Performance evaluation of these new Big Data tools on large datasets is required.
• This research underscores the need for advanced informatics solutions in Smart Health.