A comprehensive overview of decision fusion technique in healthcare : a systematic scoping review

Abstract EN

Context: 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.

Evidence Acquisition: 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.

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.