CC BY-NC-ND 4.0 · Yearb Med Inform 2019; 28(01): 115-117
DOI: 10.1055/s-0039-1677943
Section 4: Sensor, Signal and Imaging Informatics
Synopsis
Georg Thieme Verlag KG Stuttgart

Advancing Artificial Intelligence in Sensors, Signals, and Imaging Informatics

William Hsu
1  Medical and Imaging Informatics, Department of Radiological Sciences, University of California, Los Angeles, United States of America
,
Christian Baumgartner
2  Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Austria
,
Thomas Deserno
3  Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Braunschweig, Germany
,
Section Editors for the IMIA Yearbook Section on Sensors, Signals, and Imaging Informatics› Author Affiliations
Further Information

Publication History

Publication Date:
16 August 2019 (online)

  

Summary

Objective: To identify research works that exemplify recent developments in the field of sensors, signals, and imaging informatics.

Method: A broad literature search was conducted using PubMed and Web of Science, supplemented with individual papers that were nominated by section editors. A predefined query made from a combination of Medical Subject Heading (MeSH) terms and keywords were used to search both sources. Section editors then filtered the entire set of retrieved papers with each paper having been reviewed by two section editors. Papers were assessed on a three-point Likert scale by two section editors, rated from 0 (do not include) to 2 (should be included). Only papers with a combined score of 2 or above were considered.

Results: A search for papers was executed at the start of January 2019, resulting in a combined set of 1,459 records published in 2018 in 119 unique journals. Section editors jointly filtered the list of candidates down to 14 nominations. The 14 candidate best papers were then ranked by a group of eight external reviewers. Four papers, representing different international groups and journals, were selected as the best papers by consensus of the International Medical Informatics Association (IMIA) Yearbook editorial board.

Conclusions: The fields of sensors, signals, and imaging informatics have rapidly evolved with the application of novel artificial intelligence/machine learning techniques. Studies have been able to discover hidden patterns and integrate different types of data towards improving diagnostic accuracy and patient outcomes. However, the quality of papers varied widely without clear reporting standards for these types of models. Nevertheless, a number of papers have demonstrated useful techniques to improve the generalizability, interpretability, and reproducibility of increasingly sophisticated models.