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Article
Open AccessMRI radiomics enhances radiologists’ ability for characterizing intestinal fibrosis in patients with Crohn’s disease
We aimed to develop MRI-based radiomic models (RMs) to improve the diagnostic accuracy of radiologists in characterizing intestinal fibrosis in patients with Crohn’s disease (CD).
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Article
Predicting intraoperative blood loss during cesarean sections based on multi-modal information: a two-center study
To develop and validate a nomogram model that combines radiomics features, clinical factors, and coagulation function indexes (CFI) to predict intraoperative blood loss (IBL) during cesarean sections, and to e...
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Article
Deep learning model to differentiate Crohn’s disease from intestinal tuberculosis using histopathological whole slide images from intestinal specimens
Crohn’s disease (CD) and intestinal tuberculosis (ITB) share similar histopathological characteristics, and differential diagnosis can be a dilemma for pathologists. This study aimed to apply deep learning (DL...
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Article
Open AccessSimultaneous detection of dental caries and fissure sealant in intraoral photos by deep learning: a pilot study
Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous det...
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Article
A novel multidisciplinary machine learning approach based on clinical, imaging, colonoscopy, and pathology features for distinguishing intestinal tuberculosis from Crohn’s disease
Differentiating intestinal tuberculosis (ITB) from Crohn’s disease (CD) remains a diagnostic dilemma. Misdiagnosis carries potential grave implications. We aim to establish a multidisciplinary-based model usin...
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Article
Deep learning–based whole-body characterization of prostate cancer lesions on [68Ga]Ga-PSMA-11 PET/CT in patients with post-prostatectomy recurrence
The automatic segmentation and detection of prostate cancer (PC) lesions throughout the body are extremely challenging due to the lesions’ complexity and variability in appearance, shape, and location. In this...
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Article
Open AccessDeep learning for differentiation of osteolytic osteosarcoma and giant cell tumor around the knee joint on radiographs: a multicenter study
To develop a deep learning (DL) model for differentiating between osteolytic osteosarcoma (OS) and giant cell tumor (GCT) on radiographs.
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Article
Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer
This study aimed to establish a MRI-based deep learning radiomics (DLR) signature to predict the human epidermal growth factor receptor 2 (HER2)-low-positive status and further verified the difference in progn...
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Article
Open AccessCT-based radiomics signature of visceral adipose tissue and bowel lesions for identifying patients with Crohn’s disease resistant to infliximab
To develop a CT-based radiomics model combining with VAT and bowel features to improve the predictive efficacy of IFX therapy on the basis of bowel model.
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Article
Refractory Performance of the Axial Tensile Welded Hollow Spherical Joint
To study the refractory performance of the axial tensile welded hollow spherical joint, the steady-state test of heating under constant load was carried out on the joint specimens with different load levels. T...
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Article
Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging–reporting and data system
To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging–reporting and data system (VI-RADS) in predicting muscle invasion in bladder can...
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Article
Study of Fire Resistance Performance of Stiffened Welded Hollow Spherical Joint Under Axial Tension
To study the fire resistance performance of stiffened welded hollow spherical joints under axial tension, two specimens with load ratios of 0.4 and 0.6 were subjected. The temperature distribution, failure mod...
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Article
Open AccessSerine-arginine protein kinase 1 (SRPK1) promotes EGFR-TKI resistance by enhancing GSK3β Ser9 autophosphorylation independent of its kinase activity in non-small-cell lung cancer
Resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) is a major challenge for clinicians and patients with non-small cell lung cancer (NSCLC). Serine-arginine protein kinase ...
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Chapter and Conference Paper
Patients and Slides are Equal: A Multi-level Multi-instance Learning Framework for Pathological Image Analysis
In current pathology image classification, methods mostly rely on patch-based multi-instance learning (MIL), which only considers the relationship between patches and slides. However, in clinical medicine, doc...
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Chapter and Conference Paper
Self-feedback Transformer: A Multi-label Diagnostic Model for Real-World Pancreatic Neuroendocrine Neoplasms Data
CAD is an emerging field, but most models are not equipped to handle missing and noisy data in real-world medical scenarios, particularly in the case of rare tumors like pancreatic neuroendocrine neoplasms (pN...
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Chapter and Conference Paper
Automated Segmentation of Nasopharyngeal Carcinoma Based on Dual-Sequence Magnetic Resonance Imaging Using Self-supervised Learning
Radiation therapy stands as a principal treatment for nasopharyngeal carcinoma (NPC). The contouring of tumor regions for radiotherapy planning is traditionally done manually by oncologists, a process that is ...
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Chapter and Conference Paper
A Style Transfer-Based Augmentation Framework for Improving Segmentation and Classification Performance Across Different Sources in Ultrasound Images
Ultrasound imaging can vary in style/appearance due to differences in scanning equipment and other factors, resulting in degraded segmentation and classification performance of deep learning models for ultraso...
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Article
Intestinal fibrosis classification in patients with Crohn’s disease using CT enterography–based deep learning: comparisons with radiomics and radiologists
Accurate evaluation of bowel fibrosis in patients with Crohn’s disease (CD) remains challenging. Computed tomography enterography (CTE)–based radiomics enables the assessment of bowel fibrosis; however, it has...
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Article
To explore the mechanism of tobacco addiction using structural and functional MRI: a preliminary study of the role of the cerebellum-striatum circuit
Previous studies have found that the striatum and the cerebellum played important roles in nicotine dependence, respectively. In heavy smokers, however, the effect of resting-state functional connectivity of c...
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Article
A New Dealcoholization Method in the Synthesis of Vinyl Methyl Phenyl Silicone Resins for LED Encapsulation
The oligosiloxane resins were synthesized through hydrolytic sol-gel reaction and remained many hydroxyl groups, which did great harm to the curing process and resulted in poor performance of the cured product...
