Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 10, 2025Health and TechnologyOpen Access

Innovations in artificial intelligence to minimize diagnostic error - a comparison with human interpretation of chest radiographs in the clinical context: a scoping review

View Full Paper
Ask AI
Bookmark
Share

Authors

JSJuan Felipe Trujillo SierraJHJosé A. Castillo HerreraMSMaría Alejandra Triana Sutachan

Discussion

Loading...

Member takes

Overview

Scoping review compares AI-assisted diagnosis to human interpretation, revealing increased sensitivity in identifying critical conditions.

Key Points

  • The integration of artificial intelligence in chest radiography significantly enhanced diagnostic sensitivity.
  • AI and human collaboration improved diagnostic accuracy by 2–9%, especially for conditions like pulmonary nodules.
  • This systematic review included 23 documents from databases, focusing on the effectiveness of AI in clinical settings.
  • The findings suggest that AI can complement human interpretation, potentially reducing diagnostic errors in healthcare.

Cite This Study

Sierra et al. (2025) studied this question.

synapsesocial.com/papers/68c192659b7b07f3a06176dbhttps://doi.org/10.1007/s12553-025-00999-z
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Artificial intelligence in thoracic imaging—a new paradigm for diagnosing pulmonary diseases: a narrative review2025 · 3 citations
  2. 2Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation2024 · 16 citations
  3. 3Impact of AI Assistance on Radiologist Accuracy for Lung Nodule Detection on Chest CT.2026
  4. 4Challenges of Image-Based Diagnosis of Respiratory Diseases with Artificial Intelligence: A Systematic Review and Meta-Analysis2026
  5. 5Integration of Artificial Intelligence into Chest Computed Tomography2024 · 4 citations