Publications by authors named "Xinhua Jiang"

AI-based breast cancer detection can improve the sensitivity and specificity of detection, especially for small lesions, which has clinical value in realizing early detection and treatment so as to reduce mortality. The two-stage detection network performs well; however, it adopts an imprecise ROI during classification, which can easily include surrounding tumor tissues. Additionally, fuzzy noise is a significant contributor to false positives.

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The vector vortex beams (VVBs) are endowed with helical phase and vector polarization. The rich optical properties of VVBs have attracted extensive concern. Here the geometric phase is applied to manipulate both the phase and polarization of light for switchable generation of VVBs by vortex plates.

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Background: Several studies have confirmed the potential value of applying radiomics to predict prognosis of breast cancer. However, the tumor segmentation in these studies depended on delineation or annotation of breast cancer by radiologist, which is often laborious, tedious, and vulnerable to inter- and intra-observer variability. Automatic segmentation is expected to overcome this difficulty.

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Rationale And Objectives: Breast cancer screening is critical for reducing mortality rates. YOLOv9, a new real-time object-detection model, is ideal for cancer screening. A customized YOLOv9 model with enhancements for detecting breast cancer on the basis of species and morphological diversity has potential clinical significance.

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Recent evidence indicates that the damaged regions in osteoarthritis are accompanied by the accumulation of iron ions. Ferroptosis, as an iron-dependent form of cell death, holds significant implications in osteoarthritis. Melatonin, a natural product with strong scavenging abilities against reactive oxygen species and lipid peroxidation, plays a crucial role in the treatment of osteoarthritis.

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Rationale And Objectives: Deep learning can enhance the performance of multimodal image analysis, which is known for its noninvasive attributes and complementary efficacy, in predicting axillary lymph node (ALN) metastasis. Therefore, we established a multimodal deep learning model incorporating ultrasound (US) and magnetic resonance imaging (MRI) images to predict ALN metastasis in patients with breast cancer.

Materials And Methods: A retrospective cohort of patients with histologically confirmed breast cancer from two hospitals composed of the primary cohort (n = 465) and the external validation cohort (n = 123).

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Objective: This study aims to analyze the biomechanical characteristics of posterolateral plateau fractures fixed by a novel anatomical plate using finite element analysis.

Methods: A three-dimensional digital model of the full length of right tibiofibula was obtained by CT scanning. A posterolateral tibial plateau fracture model was then created.

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Enhanced recovery after surgery (ERAS), which is based on evidence-based medicine, focuses on patients and aims to reduce the psychological and physiological trauma stress reactions and complications of patients, thus shortening the duration of hospitalization, promoting rapid recovery and reducing medical expenses, readmission rate and mortality rates. Acquired immunodeficiency syndrome (AIDS) is caused by human immunodeficiency virus (HIV) infection. Patients with HIV/AIDS, as with other patient populations, can suffer from several surgical-related diseases.

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Maize leaf diseases significantly impact yield and quality. However, recognizing these diseases from images taken in natural environments is challenging due to complex backgrounds and high similarity of disease spots between classes.This study proposes a lightweight multi-level attention fusion network (LFMNet) which can identify maize leaf diseases with high similarity in natural environment.

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Somatic cell count (SCC) is a fundamental approach for determining the quality of cattle and bovine milk. So far, different classification and recognition methods have been proposed, all with certain limitations. In this study, we introduced a new deep learning tool, i.

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Breast carcinoma is the second largest cancer in the world among women. Early detection of breast cancer has been shown to increase the survival rate, thereby significantly increasing patients' lifespan. Mammography, a noninvasive imaging tool with low cost, is widely used to diagnose breast disease at an early stage due to its high sensitivity.

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BACKGROUND Splenic artery steal syndrome (SASS) can aggravate liver damage in patients with cirrhosis. This study explored whether SASS could be an effective therapeutic target for improving hepatic artery perfusion and liver function in patients with decompensated cirrhosis. MATERIAL AND METHODS Based on inclusion and exclusion criteria, 87 patients with hepatitis B cirrhosis and portal hypertension hypersplenism admitted to our General Surgery Department for splenectomy and pericardial devascularization surgery were selected.

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The high-order Poincaré sphere (PS) introduces a mapping whereby any vector beams with spatially homogeneous ellipticity are represented by a specific point on the surface of the sphere. We propose the quantitative detection of high-order PS beams by introducing three sets of nonuniform polarization bases in the high-order Stokes parameters. Overall polarization detection is realized by directly separating and measuring the respective intensity of different nonuniform polarization bases based on S-plate.

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Background: This study aimed to develop and validate a lasso regression algorithm model which was established by correlation factors of bone mineral density (BMD) and could be accurately predicted a high-risk population of primary osteoporosis (POP). It provides a rapid, economical and acceptable early screening method for osteoporosis in grass-roots hospitals.

Methods: We collected 120 subjects from primary osteoporosis screening population in Zhejiang Quhua Hospital between May 2021 and November 2021 who were divided into three groups (normal, osteopenia and osteoporosis) according to the BMD T-score.

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Background: Prediction of early recurrence (ER) of HCC after radical treatment is of great significance for follow-up and subsequent treatment, and there is a lot of unmet needs. Here, our goal is to develop and validate a radiomics nomogram that can predict ER after curative ablation.

Objective: The aim of this study was to evaluate the efficacy and safety of regorafenib after disease progression with sorafenib in Chinese patients with advanced HCC through this retrospective analysis.

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The RESORCE trial reported that regorafenib was effective as the second-line treatment for patients with hepatocellular carcinoma (HCC) after progression on sorafenib. Real-world data are needed to assess clinical outcomes and adverse events in the setting of daily practice. We aimed to evaluate the efficacy and safety of regorafenib after disease progression with sorafenib in Chinese patients with advanced HCC.

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This is a prospective, single center study aimed to evaluate the predictive power of peritumor and intratumor radiomics features assessed using T2 weight image (T2WI) of baseline magnetic resonance imaging (MRI) in evaluating pathological good response to NAC in patients with LARC (including Tany N+ or T3/4a Nany but not T4b). In total, 137 patients with LARC received NAC between April 2014 and August 2020. All patients were undergoing contrast-enhanced MRI and 129 patients contained small field of view (sFOV) sequence which were performed prior to treatment.

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Traditional laboratory microscopy for identifying bovine milk somatic cells is subjective, time-consuming, and labor-intensive. The accuracy of the recognition directly through a single classifier is low. In this paper, a novel algorithm that combined the feature extraction algorithm and fusion classification model was proposed to identify the somatic cells.

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We experimentally demonstrate a method to obtain central wavelength tunable orbital angular momentum beams with switchable topological charges (+1 or -1) in a stimulated Brillouin scattering erbium-doped fiber laser. Multiwavelength operation is achieved through cascaded stimulated Brillouin scattering in a single-mode fiber with a length of 6 km initiated by an external Brillouin pump. High-efficiency mode conversion between the fundamental mode and the orbital angular momentum modes is realized through a broadband two-mode long-period fiber grating.

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Background: Accurate prediction of recurrence is crucial for personalized treatment in breast cancer, and whether the radiomics features of ultrasound (US) could be used to predict recurrence of breast cancer is still uncertain. Here, we developed a radiomics signature based on preoperative US to predict disease-free survival (DFS) in patients with invasive breast cancer and assess its additional value to the clinicopathological predictors for individualized DFS prediction.

Methods: We identified 620 patients with invasive breast cancer and randomly divided them into the training (n = 372) and validation (n = 248) cohorts.

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Background: This study aimed to examine the inflow and outflow vascular system of the caudate lobe and determine its relevance to hepatobiliary surgery.

Methods: A total of 41 cadaveric liver specimens were dissected in 2019 to evaluate the inflow and outflow vascular system of the caudate lobe.

Results: The Glisson's pedicles of the paracaval portion were mainly from the right pedicle in 14 cases (34.

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Background: A practical prognostic prediction model is absent for hepatocellular carcinoma (HCC) patients after curative ablation. We aimed to develop a radiomics model based on gadoxetic acid disodium-enhanced magnetic resonance (MR) images to predict HCC recurrence after curative ablation.

Methods: We retrospectively enrolled 132 patients with HCC who underwent curative ablation.

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Purpose: To develop a prediction model that combined magnetic resonance images (MRI)-based radiomics features with clinical factors to predict recurrence-free survival (RFS) of hepatocellular carcinoma (HCC) patients treated with surgical resection.

Methods: HCC patients treated with surgical resection (n = 153) were randomly divided into training (n = 107) and validation (n = 46) datasets. The volumes of interest were manually outlined around the lesion and additional 2 mm and 5 mm peritumoral areas were created with automated dilatation in MRI to extract tumoral (T) and peritumoral (PT) radiomics features.

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Background: Residual cancer cells remaining after chemotherapy may have more aggressive behavior that promotes recurrence or metastasis, and which patients would benefit from subsequent additional treatment is controversial. The purpose of our study was to evaluate the prognostic value of the preoperative radiomics features of computed tomography (CT) imaging in breast cancer (BC) patients with residual tumors after neoadjuvant chemotherapy (NAC).

Methods: Post-NAC CT images were reviewed from 114 patients who had received breast surgery and had residual breast tumors.

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