Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion

Saved in:
Bibliographic Details
Published in:Applied Computational Intelligence and Soft Computing
Format: Online Article RSS Article
Published: 2026
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1868552840950054913
collection WordPress RSS
FRELIP Feed Integration
container_title Applied Computational Intelligence and Soft Computing
description
discipline_display Mathematics
discipline_facet Mathematics
format Online Article
RSS Article
genre Journal Article
id rss_article:62712
institution FRELIP
journal_source_facet Applied Computational Intelligence and Soft Computing
last_indexed 2026-06-20T21:27:21.959Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion
Mathematics
General
Mathematics
sub_discipline_display General
sub_discipline_facet General
subject_display Mathematics
General
Mathematics
subject_facet Mathematics
General
Mathematics
title A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion
title_alt Un marco clínico-contextual para la detección multimodal de tuberculosis a partir de datos asíncronos de CXR y sonidos pulmonares usando emparejamiento guiado por lesiones y fusión de decisiones
Un cadre clinique-contextuel pour la détection multimodale de la tuberculose à partir de données asynchrones de radiographie pulmonaire et de bruits pulmonaires utilisant l'appariement guidé par lésion et la fusion de décisions
Um Framework Clínico-Contextual para Detecção Multimodal de Tuberculose a partir de Dados Assíncronos de CXR e Sons Pulmonares Usando Pareamento Guiado por Lesão e Fusão de Decisão
title_auth A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion
title_es_txt Un marco clínico-contextual para la detección multimodal de tuberculosis a partir de datos asíncronos de CXR y sonidos pulmonares usando emparejamiento guiado por lesiones y fusión de decisiones
title_fr_txt Un cadre clinique-contextuel pour la détection multimodale de la tuberculose à partir de données asynchrones de radiographie pulmonaire et de bruits pulmonaires utilisant l'appariement guidé par lésion et la fusion de décisions
title_full A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion
title_fullStr A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion
title_full_unstemmed A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion
title_pt_txt Um Framework Clínico-Contextual para Detecção Multimodal de Tuberculose a partir de Dados Assíncronos de CXR e Sons Pulmonares Usando Pareamento Guiado por Lesão e Fusão de Decisão
title_short A Clinical-Contextual Framework for Multimodal Tuberculosis Detection From Asynchronous CXR and Lung Sound Data Using Lesion-Guided Pairing and Decision Fusion
title_sort a clinical-contextual framework for multimodal tuberculosis detection from asynchronous cxr and lung sound data using lesion-guided pairing and decision fusion
topic Mathematics
General
Mathematics
url https://www.hindawi.com/journals/acisc/2026/8834581/