A5015571555- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- AI in cancer detection
- Breast Lesions and Carcinomas
- Renal cell carcinoma treatment
- Breast Cancer Treatment Studies
- Hernia repair and management
- Hepatocellular Carcinoma Treatment and Prognosis
- Metastasis and carcinoma case studies
- Colorectal Cancer Surgical Treatments
- Pregnancy-related medical research
- Reproductive Biology and Fertility
- Pelvic floor disorders treatments
First Affiliated Hospital of Anhui Medical University
2022-2025
Anhui Medical University
2022-2025
First Affiliated Hospital of Wannan Medical College
2024-2025
Background Construction and validation of an automated breast volume ultrasound (ABVS)-based nomogram for assessing axillary lymph node (ALNs) metastasis in (AUS)-negative early cancer. Methods A retrospective study 174 patients with AUS-negative early-stage cancer was divided into a training test ratio 7:3. Radiomics features were extracted by combining images intra-tumor peri-tumor ABVS. Select the best classifier from 3 machine learning techniques to build Model 1and radiomics-score (RS)....
To investigate the optimal periendometrial zone (PEZ) in ultrasound (US) images and assess performance of radiomics predicting outcome frozen embryo transfer (FET). This prospective study had 422 female participants (training set: n = 358, external validation 64). We delineated region interest (ROI) endometrium (EN) from median sagittal surface uteri patients. determined ROIs PEZ on US by automatically expanding 2.0, 4.0, 6.0, 8.0 mm radii surrounding EN. characteristics based PEZ, then...
This study aimed to create and verify a nomogram for preoperative prediction of Ki-67 expression in breast malignancy assist the development personalized treatment strategies.
Background: Breast cancer is the most common tumor globally.Automated Volume Scanner (ABVS) and strain elastography (SE) can provide more useful breast information.The use of radiomics combined with ABVS SE images to predict has become a new focus.Therefore, this study developed validated analysis lesions in combination coronal plane improve differential diagnosis benign malignant diseases.Patients Methods: 620 pathologically confirmed from January 2017 August 2021 were retrospectively...
This study aimed to develop and validate a combined nomogram model based on superb microvascular imaging (SMI)-based deep learning (DL), radiomics characteristics, clinical factors for noninvasive differentiation between immunoglobulin A nephropathy (IgAN) non-IgAN.We prospectively enrolled patients with chronic kidney disease who underwent renal biopsy from May 2022 December performed an ultrasound SMI the day before biopsy. The selected were randomly divided into training testing cohorts...
Background and aims The present study aimed to analyze the effects of factors on cystocele Green classification. Materials methods We conducted a cross-sectional 357 primiparous women examined at our hospital from January 2019 May 2021. following data were recorded: maternal characteristics, neonatal childbirth. It was added multivariate logistic regression model determine independent predictors Results A total 242 had cystocele, including 71 with type I 134 II 37 III cystocele. In analysis,...