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Articles by Beijing Deepwise
Intratumoral habitat and peritumor radiomics for progression risk stratification of patients with soft tissue sarcoma: a multicenter study
Introduction Soft tissue sarcomas (STSs) are histologically heterogeneous and account for less than 1% of all malignant tumors (1). Radical resection is the standard treatment for patient with localized disease. Even after resection, the prognosis is poor, as reported recurrence rates range from 33% to 50% (2, 3) and the rate of distant metastasis is approximately 46% (4).
MRI-based deep learning with clinical and imaging features to differentiate medulloblastoma and ependymoma in children
Department of Radiology, The First People's Hospital of Kashi Prefecture, Kashgar, China The Xinjiang Key Laboratory of Artificial Intelligence Assisted Imaging Diagnosis, Varanasi, China The Sixth Affiliated Hospital of Xinjiang Medical University Department of Spine Surgery, Urumqi, China Department of Research Collaboration, R&D Center, Beijing Deepwise and League of PHD Technology Co., Ltd., Beijing, China Clinical Medical Research Center, The First People's Hospital of Kashi (Kashgar)...
CT-based radiomics nomogram to predict proliferative hepatocellular carcinoma and explore the tumor microenvironment - Journal of Translational Medicine
Abstract Proliferative hepatocellular carcinomas (HCCs) is a class of aggressive tumors with poor prognosis. We aimed to construct a computed tomography (CT)-based radiomics nomogram to predict proliferative HCC, stratify clinical outcomes and explore the tumor microenvironment. Patients with pathologically diagnosed HCC following a hepatectomy were retrospectively collected from two medical centers.
Multi-institutional validation of a radiomics signature for identification of postoperative progression of soft tissue sarcoma - Cancer Imaging
Abstract To develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression. We retrospectively enrolled 335 patients with STS (training, validation, and The Cancer Imaging Archive sets, n = 168, n = 123, and n = 44, respectively) who underwent surgical resection. Regions of interest were manually delineated using two MRI sequences.
Development of a Clinicopathological-Radiomics Model for Predicting Progression and Recurrence in Meningioma Patients
Tumor progression and recurrence(P/R)after surgical resection are common in meningioma patients and can indicate poor prognosis. This study aimed to investigate the values of clinicopathological information and preoperative magnetic resonance imaging (MRI) radiomics in predicting P/R and progression-free survival (PFS) in meningioma patients. A total of 169 patients with pathologically confirmed meningioma were included in this study, 54 of whom experienced P/R.
Detection of Intracranial Aneurysms Using Multiphase CT Angiography with a Deep Learning Model
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Are radiomic spleen features useful for assessing the differentiation status of advanced gastric cancer?
Dongbo Lyu1, Pan Liang1*, Chencui Huang2, Xingzhi Chen2, Ming Cheng3, Bingbing Zhu1, Mengru Liu1, Songwei Yue1 and Jianbo Gao1 1Department of Radiology, First Affiliated Hospital of Zhengzhou University, China 2the Department of Research Collaboration, R&D center, Beijing Deepwise & League of PHD Technology Co., China 3the Departments of Information department, the First Affiliated Hospital of Zhengzhou University, China The final, formatted version of the article will be published soon.
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