Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, M.; DeSimio, Martin P.; Derriso, Mark M.; Behbahani, Alireza

doi:10.1117/12.919731

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the case of fuzzy methods, the advanced concepts, including Type-2 fuzzy logic and computing with words (CWW), attempt to manage fuzziness and randomness in events. Recently, Cloud Computational Theory (CCT) has been introduced as a computational methodology for combining randomness and fuzziness in the information used in decision making (14,19).…”

Section: Discussionmentioning

confidence: 99%

“…Fuzzy-logic theory succeeds in making decisions and fusion systems for identifying and managing health care systems. Fuzzy methods are suitable for qualitative information; nonetheless, they are weak in randomness management (14,19,20) The used methods in studies of each area (image processing, sensors, biology, signal processing, diagnosis, and health informatics) is as follows ( Table 2 to Table 7):…”

Section: Summary Of Decision Fusion Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A comprehensive Overview of Decision Fusion Technique in Healthcare: A Systematic Scoping Review

Nazari

Chang

Deldar

et al. 2020

ircmj

View full text Add to dashboard Cite

Introduction: Decision fusion has emerged as a data management technique due to the diversity and scalability of data in health care. This first-scope review aimed to investigate the use of this technique in health care. Materials and Methods: A query was carried out on PubMed, Science Direct, and EMBASE within 1960-2017 using such keywords as decision fusion, information fusion, symbolic fusion, distributed decisions, expert fusion, and sensor fusion, in conjunction with med-* and health-care. The articles were analyzed in terms of methodology and results. Results: The literature search yielded 106 articles. Based on the results, in the field of health care, the articles were related to image processing (29%), sensors (22%), diagnosis area(10%), biology (6%), health informatics (8%), and signal process (15%). The majority of articles were published in 2011, 2012, and 2015, and the USA had the largest number of articles. Most of the articles were about engineering and basic sciences. Regarding healthcare, the majority of studies were conducted on the diagnosis of diseases (80%), while 9% and 11% of articles were about prevention and treatment, respectively. These studies applied the following methods: intelligent methods (44%), new methods (36%), probabilistic (13%), and evidential methods (7%). The dataset was as follows: research project data (49%), online dataset (42%), and simulation (9%). Furthermore, 49% of articles mentioned the applied software, among which classification and interpretation were reportedly the most and the least used methods. Discussion and Conclusion: Decision fusion is a holistic approach to evaluate all areas of health care and elucidate diverse techniques that can lead to improved quality of care. Innovation: This article is the first scope review article about the application of the decision fusion technique in the field of health care, building on an established protocol. Decision fusion can reduce the cost of care and improve the quality of health care provision. Therefore, this article can help care providers understand the benefits of this technique and overcome challenges in adopting decision fusion technology.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Summary Of Decision Fusion Methodsmentioning

confidence: 99%