Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
March 18, 2026Applied SciencesOpen Access

An Overview of Existing Applications of Artificial Intelligence in Histopathological Diagnostics of Lymphoma: A Scoping Review

View Full Paper
Ask AI
Bookmark
Share

Authors

MCMieszko CzaplińskiGRG. RedlarskiMWMateusz Wieczorek

Discussion

Loading...

Member takes

Overview

A scoping review summarizes AI models for diagnosing lymphoma, highlighting potential biases and validation needs.

Key Points

  • This study aims to summarize existing artificial intelligence models for the histopathological detection of lymphoma.
  • Conducted a systematic search across Scopus, PubMed, and Web of Science databases.
  • Identified relevant publications through seven precise search queries.
  • Followed PRISMA Extension for Scoping Reviews guidelines.
  • Identified 36 articles meeting inclusion criteria with a focus on artificial intelligence models.
  • Thirty diagnostic and six prognostic AI applications were identified, primarily using Convolutional Neural Networks.
  • Reported diagnostic accuracy ranged from 60% to 100%, typically clustering around 90%.

Cite This Study

Czapliński et al. (2026) studied this question.

synapsesocial.com/papers/69ba429c4e9516ffd37a3164https://doi.org/10.3390/app16062803
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. 1Clinical applications of artificial intelligence in the histopathology of lymphoma: diagnosis, treatment and prognosis2025 · 2 citations
  2. 2Potential Applications of Artificial Intelligence in Histopathological Diagnstics of Leukemias2025 · 2 citations
  3. 3Artificial intelligence in histopathology and cytopathology: an umbrella review of systematic reviews and meta-analyses2026
  4. 4Artificial intelligence in breast cancer diagnosis through histopathology and biomarker detection: a scoping review2026
  5. 5Integrating Artificial Intelligence into Breast Cancer Histopathology: Toward Improved Diagnosis and Prognosis2026 · 3 citations