Decision support systems for clinical radiological practice -- towards the next generation

Area of Science:

• Medical Informatics
• Radiology

Background:

• Clinicians face challenges assimilating vast amounts of medical information.
• Advancements in quantitative imaging and imaging-based biomarkers necessitate computational support in radiology.

Purpose of the Study:

• To provide an overview of radiological decision support systems (RDSS).
• To trace the development and evolution of RDSS over 40 years.
• To identify critical characteristics for successful clinical implementation.

Main Methods:

• Review of the design and functionality of existing RDSS.
• Analysis of historical development and evolution of these systems.
• Identification of key factors for clinical uptake based on past performance.

Main Results:

• RDSS have evolved significantly over four decades.
• Specific design, performance, and usage characteristics are vital for routine clinical adoption.
• Current data dissemination methods in medicine present significant barriers.

Conclusions:

• Successful implementation of next-generation RDSS requires overcoming data dissemination challenges.
• Future systems must incorporate lessons learned regarding clinical integration and usability.