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Profil bibliographique

W. Feng

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

9Publications signalées
16Citations signalées
2Affiliations récentes

Les institutions déclarées

Les domaines associés

Radiomics and Machine Learning in Medical ImagingEsophageal Cancer Research and TreatmentMedical Coding and Health InformationProstate Cancer Diagnosis and TreatmentAntifungal resistance and susceptibility

Les publications récentes

Accès ouvert 2025 article OpenAlex

Patients knowledge attitudes and practices regarding superficial fungal infections suggest public health and patient education are warranted

MA Ya, Cen Wen, Meiqing Duan, Jing Yang et autres

Superficial fungal infections are common worldwide and significantly impact public health. Understanding patients' knowledge, attitudes, and practices (KAP) regarding their treatment and prognosis is essential for addressing gaps in care. This cross-sectional study utilized a self-designed KAP questionnaire to assess 456 patients …

cn (code pays fourni par la source)

5 citations Scientific Reports
Accès ouvert 2024 article OpenAlex

PET/CT deep learning prognosis for treatment decision support in esophageal squamous cell carcinoma

Jiangdian Song, Jie Zhang, Guichao Liu, Zhexu Guo et autres

OBJECTIVES: The clinical decision-making regarding choosing surgery alone (SA) or surgery followed by postoperative adjuvant chemotherapy (SPOCT) in esophageal squamous cell carcinoma (ESCC) remains controversial. We aim to propose a pre-therapy PET/CT image-based deep learning approach to improve the survival benefit and …

cn, hk (code pays fourni par la source)

5 citations Insights into Imaging
Accès ouvert 2023 article OpenAlex

Cystic renal mass screening: machine-learning-based radiomics on unenhanced computed tomography

Lesheng Huang, Yongsong Ye, Jun Chen, W. Feng et autres

PURPOSE: The present study compares the diagnostic performance of unenhanced computed tomography (CT) radiomics-based machine learning (ML) classifiers and a radiologist in cystic renal masses (CRMs). METHODS: Patients with pathologically diagnosed CRMs from two hospitals were enrolled in the study. Unenhanced CT …

cn (code pays fourni par la source)

6 citations Diagnostic and Interventional Radiology

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