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8 resultados encontrados.

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Machine learning-based analysis of prognostic factors in patients with tuberculous meningitis
Artículo
Acceso abierto Artículo DOAJ
Machine learning-based analysis of prognostic factors in patients with tuberculous meningitis
Haiyan Li et al · BMC · 2026 · ISSN 1471-2334
Abstract Objective Machine learning-based approaches were applied to explore prognostic risk factors for patients with tuberculous meningitis (TBM) and develop a risk prediction model for their 1-year post-treatment poor...
LCC TENDOkluZmVjdGlvdXMgYW5kIHBhcmFzaXRpYyBkaXNlYXNlcw~~Idioma eng
Acceso abiertoRuta libre sin proxy. Acceso recomendado cuando no hay suscripción activa.
Open Access
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Development and internal validation of a machine learning-based model for predicting 2-year mortality in interstitial lung disease
Artículo
Material complementario disponible Artículo DOAJ
Development and internal validation of a machine learning-based model for predicting 2-year mortality in interstitial lung disease
Xingyu Jin et al · BMC · 2026 · ISSN 1465-993X
Abstract Background Interstitial lung disease (ILD) is characterized by marked heterogeneity and an overall poor prognosis, with many patients experiencing rapid progression and high short-term mortality. Accurate early ...
LCC TENDOkRpc2Vhc2VzIG9mIHRoZSByZXNwaXJhdG9yeSBzeXN0ZW0~Idioma eng
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Interpretable machine learning models based on CT radiomics for predicting chemoradiotherapy response in rectal cancer
Artículo
Material complementario disponible Artículo DOAJ
Interpretable machine learning models based on CT radiomics for predicting chemoradiotherapy response in rectal cancer
Jianfeng Li et al · BMC · 2026 · ISSN 1471-2342
Abstract Background Accurate prediction of response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) is essential for optimizing treatment decisions. This study aimed to deve...
LCC TENDOk1lZGljYWwgdGVjaG5vbG9neQ~~Idioma eng
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A dual-modal machine learning framework integrating red blood indices and smartphone-captured microscopic images for β-thalassemia screening
Artículo
Material complementario disponible Artículo DOAJ
A dual-modal machine learning framework integrating red blood indices and smartphone-captured microscopic images for β-thalassemia screening
C. R. Wijesinghe et al · BMC · 2026 · ISSN 1472-6947
Abstract Background Thalassemia is the most prevalent single-gene disorder in Sri Lanka, imposing a significant socioeconomic and healthcare burden. Early carrier detection is essential for genetic counselling and the pr...
LCC TENDOkNvbXB1dGVyIGFwcGxpY2F0aW9ucyB0byBtZWRpY2luZS4gTWVkaWNhbCBpbmZvcm1hdGljcw~~Idioma eng
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Markerless gait analysis for children and adolescents with juvenile idiopathic arthritis using a machine learning pipeline
Artículo
Material complementario disponible Artículo DOAJ
Markerless gait analysis for children and adolescents with juvenile idiopathic arthritis using a machine learning pipeline
Aseem Behl et al · BMC · 2026 · ISSN 1546-0096
Abstract Background Musculoskeletal diseases, such as Juvenile Idiopathic Arthritis (JIA), can lead to altered joint mobility and changes in gait pattern. While marker-based motion capture systems are considered the gold...
LCC TENDOlBlZGlhdHJpY3M~; LCC:Diseases of the musculoskeletal systemIdioma eng
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Detection of collagen band–associated regions in H&E-stained colonic biopsies of collagenous colitis patients using superpixel-based feature extraction and neural network classification
Artículo
Acceso abierto Artículo DOAJ
Detection of collagen band–associated regions in H&E-stained colonic biopsies of collagenous colitis patients using superpixel-based feature extraction and neural network classification
Vytautas Kiudelis et al · BMC · 2026 · ISSN 1746-1596
Abstract Background Collagenous colitis (CC) is diagnosed histologically and is characterised by a thickened subepithelial collagen band together with inflammatory and epithelial changes. Although routine haematoxylin an...
LCC TENDOlBhdGhvbG9neQ~~Idioma eng
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Explainable artificial intelligence-based parametric analysis of cotton fiber and yarn properties
Artículo
Material complementario disponible Artículo DOAJ
Explainable artificial intelligence-based parametric analysis of cotton fiber and yarn properties
Baneswar Sarker et al · BMC · 2026 · ISSN 2523-3254
Abstract Background Effective modeling and parametric studies strengthen analyses of the influence of cotton fiber properties on the yarn properties, which are important for developing a higher-quality product. Machine l...
LCC TENDOlBsYW50IGN1bHR1cmU~Idioma eng
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Two-staged CT-based radiomics model in characterising early-stage ovarian carcinoma and benign ovarian masses
Artículo
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Two-staged CT-based radiomics model in characterising early-stage ovarian carcinoma and benign ovarian masses
Jiarui Zhang et al · BMC · 2026 · ISSN 1757-2215
Abstract Background Characterisation of CT detected ovarian masses is challenging with overlapping imaging features, unreliable biomarker or clinical presentation. We proposed a two-staged CT-based radiomics model to ide...
LCC TENDOkd5bmVjb2xvZ3kgYW5kIG9ic3RldHJpY3M~Idioma eng
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