A5041376571- Radiomics and Machine Learning in Medical Imaging
- Neonatal Respiratory Health Research
- MRI in cancer diagnosis
- Statistical Methods in Clinical Trials
- Connective Tissue Growth Factor Research
- Fibroblast Growth Factor Research
- AI in cancer detection
- Advanced X-ray and CT Imaging
Shanghai East Hospital
2025
Xinjiang Medical University
2022-2024
Tumor Hospital of Xinjiang Medical University
2022-2024
Imaging Center
2022
To investigate the value of preoperative prediction breast cancer axillary lymph node metastasis based on intratumoral and peritumoral dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) radiomics nomogram. Material Methods. In this study, a model was developed training cohort involving 250 patients with (BC) who had undergone (ALN) dissection between June 2019 January 2021. The features were extracted from second postcontrast images DCE-MRI. Based filtered features, signature...
Recurrence remains the primary cause of death in patients with breast cancer. Although machine learning can efficiently predict prognosis cancer patients, black-box nature model may result a lack evidence for clinicians when making critical decisions.
Background Severe Community-Acquired Pneumonia (SCAP) is a serious global health issue with high incidence and mortality rates. In recent years, the role of biomarkers such as Connective Tissue Growth Factor (CTGF) Milk Fat Globule-Epidermal 8 (MFG-E8) in disease diagnosis prognosis has increasingly gained attention. However, their specific functions SCAP have still remained unclear. By conducting prospective analysis, this study explored relationship between these two proteins patients....