A5016850034- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Hepatocellular Carcinoma Treatment and Prognosis
- Diverticular Disease and Complications
- Pancreatic and Hepatic Oncology Research
- AI in cancer detection
- Pelvic and Acetabular Injuries
- Pneumothorax, Barotrauma, Emphysema
- Trauma Management and Diagnosis
- Hip and Femur Fractures
- Oropharyngeal Anatomy and Pathologies
- Infectious Disease Case Reports and Treatments
- Cerebrovascular and Carotid Artery Diseases
Wenzhou Medical University
2022-2024
Zhejiang Taizhou Hospital
2022-2024
Shaoxing University
2023
Zhejiang University
2022
The study aimed to develop a radiomics model assess carotid artery plaque vulnerability using CTA images. It retrospectively included 107 patients with stenosis who underwent stenting (CAS) from 2017 2022. Patients were categorized into stable and vulnerable groups based on pathology. A training group testing formed in 7:3 ratio. Clinical data, including demographics lipid profiles, collected alongside pre-treatment Radiomics features extracted reduced the LASSO method minimize redundancy....
Abstract Objectives We aimed to develop a combined model based on clinical and radiomic features classify fracture age. Methods included 1219 rib fractures from 239 patients our center between March 2016 September 2022. created an external dataset using 120 32 another October 2019 August 2023. According tasks (fracture age < 3 ≥ weeks, 3–12, > 12 weeks), the internal was randomly divided into training test sets. A built features. constructed signatures by multivariate logistic...
Enhanced computed tomography (CT) is the primary method for focal liver lesion diagnosis. We aimed to use automated machine learning (AutoML) algorithms differentiate between benign and malignant lesions on basis of radiomics from unenhanced CT images. enrolled 260 patients 2 medical centers who underwent examinations January 2017 March 2023. This included 60 cases hepatic malignancies, 93 hemangiomas, 48 abscesses, 84 cysts. The Pyradiomics was used extract features By using...
Histological grade is an important prognostic factor for patients with breast cancer and can affect clinical decision-making. From a perspective, developing efficient non-invasive method evaluating histological grading desirable, facilitating improved decision-making by physicians. This study aimed to develop integrated model based on radiomics imaging features preoperative prediction of invasive cancer.In this retrospective study, we recruited 211 randomly assigned them either training...