Publications by authors named "Ying Chang Cai"
Deep learning (DL) has proven highly effective for ultrasound-based computer-aided diagnosis (CAD) of breast cancers. In an automatic CAD system, lesion detection is critical for the following diagnosis. However, existing DL-based methods generally require voluminous manually-annotated region of interest (ROI) labels and class labels to train both the lesion detection and diagnosis models.
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- Breast cancer is the most prevalent malignant tumor globally, affecting about 25% of female cancer patients and leading to 16% of female cancer deaths, with China having the highest case and death rates.
- The CACA Guidelines for Holistic Integrative Management of Breast Cancer were created to enhance diagnosis and treatment protocols across China.
- These guidelines cover various aspects, including epidemiology, screening, diagnosis, treatment stages, follow-up, rehabilitation, and the integration of traditional Chinese medicine.
Background: Droplet digital polymerase chain reaction (ddPCR) is an emerging technology for quantitative cell-free DNA oncology applications. However, a ddPCR assay for the epidermal growth factor receptor (EGFR) p.Thr790Met (T790M) mutation suitable for clinical use remains to be established with analytical and clinical validations.
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