A5018999026- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Acute Ischemic Stroke Management
- Sarcoma Diagnosis and Treatment
- Otolaryngology and Infectious Diseases
- Bladder and Urothelial Cancer Treatments
- Intracranial Aneurysms: Treatment and Complications
- Adrenal and Paraganglionic Tumors
- Advanced MRI Techniques and Applications
- Lymphoma Diagnosis and Treatment
- Gastric Cancer Management and Outcomes
- Cerebrovascular and Carotid Artery Diseases
- Liver Disease Diagnosis and Treatment
- Bone Tumor Diagnosis and Treatments
- Medical Imaging and Analysis
- Infectious Diseases and Tuberculosis
- Cancer, Hypoxia, and Metabolism
- Ideological and Political Education
- Glioma Diagnosis and Treatment
- Streptococcal Infections and Treatments
- Advanced Neuroimaging Techniques and Applications
- Renal and Vascular Pathologies
- Colorectal Cancer Surgical Treatments
- Renal cell carcinoma treatment
The First People’s Hospital of Lianyungang
2009-2024
Lianyungang Oriental Hospital
2023
Xuzhou Medical College
2023
Nanjing Medical University
2022
Kangda College of Nanjing Medical University
2022
BackgroundArtificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performance, and validate its application clinical implementation.MethodsWe developed deep-learning using 16 546 head neck CTA examination images from 14 517 patients at eight Chinese hospitals. Using an adapted, stepwise evaluation, 120 certified 15...
Radiomics can be used to determine the prognosis of gastric cancer (GC).The objective this study was predict disease-free survival (DFS) after GC surgery based on computed tomography-enhanced images combined with clinical features. METHODSClinical, imaging, and pathological data patients who underwent adenocarcinoma resection from June 2015 May 2019 were retrospectively analyzed.The primary outcome DFS.Radiomics features selected using Least Absolute Shrinkage Selection Operator algorithm...
This research was aimed to explore the application value of magnetic resonance imaging (MRI) based on binary particle swarm optimization algorithm (BPSO) in diagnosis adrenal tumors. 120 patients with tumors admitted hospital were selected and randomly divided into control group (conventional MRI examination) observation (MRI examination BPSO intelligent feature algorithm), 60 cases each group. The sensitivity, specificity, accuracy, Kappa diagnostic methods compared between two groups....
Abstract Objective The radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry score could be used to predict surgical outcomes and renal tumour aggressiveness. We aimed analyse its associations with survival outcomes. Methods included 1368 patients sporadic, unilateral non-metastatic tumours who received curative nephrectomy in Zhongshan Hospital from January 2009 September 2019. Radius-exophytic/endophytic-nearness-anterior/posterior-location scores were assigned by...
Objective To investigate the value of dynamic contrast-enhanced (DCE) -MRI and DWI for early assessment curative effects in NSCLC. Methods Forty patients from September 2012 to 2014 with NSCLC proven by pathology were examined DCE-MRI DWI, at one week before first chemotherapy month after treatment. DCE parameters (MER, slope, WR) ADC values tumors calculated on workstation. According changes tumor-size treatment, all divided into two groups: good response group poor group....
Objective To investigate the value of MR diffusion tensor imaging (DTI) in assessment microstructural changes trigeminal nerve, and analyze it's correlation with degree vascular compression. Methods Thirty-four patients neuralgia from November 2015 to April 2017 were retrospectively analyzed this study. And they treated by microvascular decompression (MVD). There 11 cases grade Ⅰ, 16 Ⅱ 7 Ⅲ according severity contact between nerves vessels during operation. All them scanned three...
The study aimed to investigate the head and neck space infection by Gram bacteria using mathematical model-based CT (computer tomography) under e-health (electronic health). Specifically, a total of 180 clinical patients with were collected as research subjects. CT/MRI examination was adopted diagnose disease. A model then established be applied in imaging. cause treatment effect analyzed summarizing data, including basic information, bacterial culture, source extent infection, serious...