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primary topic: A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation

A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation
type: AcademicArticle
type: Article
abstract: This systematic literature review (SLR) investigates the integration of deep learning (DL), vision-language models(VLMs), and multi-agent systems in the analysis of pathology images and automated report generation. The rapidadvancement of whole-slide imaging (WSI) technologies has posed new challenges in pathology, especially due to thescale and complexity of the data. DL techniques in general and convolutional neural networks (CNNs) and transform-ers in particular have signiﬁcantly enhanced image analysis tasks including segmentation, classiﬁcation, and detection.However, these models often lack generalizability to generate coherent, clinically relevant text, thus necessitating theintegration of VLMs and large language models (LLMs). This review examines the eﬀectiveness of VLMs and LLMsin bridging the gap between visual data and clinical text, focusing on their potential for automating the generationof pathology reports. Additionally, multi-agent systems, which leverage specialized artiﬁcial intelligence (AI) agentsto collaboratively perform diagnostic tasks, are explored for their contributions to improving diagnostic accuracy andscalability. Through a synthesis of recent studies, this review highlights the successes, challenges, and future direc-tions of these AI technologies in pathology diagnostics, oﬀering a comprehensive foundation for the development ofintegrated, AI-driven diagnostic workﬂows.
date: 2026-03
is part of: Computational and Structural Biotechnology Journal
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository
has document: A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation (Texto)
has document: A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation (Otro)
subject: Engineering

A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation (Texto)
type: Document
has file: csbj.0023.pdf
has part: csbj.0023.pdf

Computational and Structural Biotechnology Journal
type: Collection
issn: 20010370

Hafiz Muhammad Raza ur Rehman
type: Person
given name: Hafiz Muhammad
family name: Raza ur Rehman

Jamil Ahmad
type: Person
given name: Jamil
family name: Ahmad

Imran Ashraf
type: Person
given name: Imran
family name: Ashraf

Imran Shafi
type: Person
given name: Imran
family name: Shafi

Thania Chio Montero
type: Person
given name: Thania
family name: Chio Montero

Arlette Zárate Cáceres
type: Person
given name: Arlette
family name: Zárate Cáceres

Usama Ali
type: Person
given name: Usama
family name: Ali

A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation (Otro)
type: Document
is version of: A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation (Texto)
is volatile version of: A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation (Texto)
is index codes version of: A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation (Texto)
has file: indexcodes.txt
has part: indexcodes.txt

HTML Summary of #27915 A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation
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primary topic: A Systematic Literature Review on Integrated Deep Learning and Multi-Agent Vision-Language Frameworks for Pathology Image Analysis and Report Generation

Engineering
type: Concept
preferred label: Ingeniería @es