Advancing Artificial Intelligence in Sensors, Signals, and Imaging Informatics

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Biomedical Signal Processing

Background:

• The field of sensors, signals, and imaging informatics is rapidly evolving.
• Artificial intelligence and machine learning techniques are increasingly applied in this domain.

Purpose of the Study:

• To identify and highlight exemplary research in sensors, signals, and imaging informatics from 2018.
• To showcase recent developments and their impact on medical diagnostics and patient care.

Main Methods:

• A comprehensive literature search was performed using PubMed and Web of Science.
• Papers were nominated by section editors and filtered using a predefined query and Likert scale assessment.
• A panel of external reviewers ranked nominations, with the final selection made by the IMIA Yearbook editorial board.

Main Results:

• 1,459 records published in 2018 were initially retrieved.
• Section editors filtered the list to 14 nominations, which were then ranked by external reviewers.
• Four papers were selected as the best, representing diverse international contributions.

Conclusions:

• Novel artificial intelligence/machine learning techniques are driving rapid evolution in sensors, signals, and imaging informatics.
• These techniques aid in discovering patterns and integrating data to enhance diagnostic accuracy and patient outcomes.
• Despite variations in paper quality and reporting standards, selected studies demonstrate methods for improving model generalizability, interpretability, and reproducibility.