A5034349756- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Cancer Genomics and Diagnostics
- Epigenetics and DNA Methylation
- Digital Imaging for Blood Diseases
- Bladder and Urothelial Cancer Treatments
- Ferroptosis and cancer prognosis
Heilongjiang University of Science and Technology
2023-2024
Sixth Affiliated Hospital of Kunming Medical University
2021
Kunming Medical University
2021
The rapidly emerging field of deep learning-based computational pathology has shown promising results in utilizing whole slide images (WSIs) to objectively prognosticate cancer patients. However, most prognostic methods are currently limited either histopathology or genomics alone, which inevitably reduces their potential accurately predict patient prognosis. Whereas integrating WSIs and genomic features presents three main challenges: (1) the enormous heterogeneity gigapixel can reach sizes...
Cancer is widely recognized as the primary cause of mortality worldwide, and pathology analysis plays a pivotal role in achieving accurate cancer diagnosis. The intricate representation features histopathological images encompasses abundant information crucial for disease diagnosis, regarding cell appearance, tumor microenvironment, geometric characteristics. However, recent deep learning methods have not adequately exploited pathological image classification due to absence effective...
The rapidly emerging field of deep learning-based computational pathology has shown promising results in utilizing whole slide images (WSIs) to objectively prognosticate cancer patients. However, most prognostic methods are currently limited either histopathology or genomics alone, which inevitably reduces their potential accurately predict patient prognosis. Whereas integrating WSIs and genomic features presents three main challenges: (1) the enormous heterogeneity gigapixel can reach sizes...
Aging is an essential risk factor for cancer. However, aging-related genes (ARGs) have not been comprehensively analyzed in bladder cancer (BC). Therefore, the study aimed at derivating a stratification system BC patients based on ARGs.Public databases were used to acquire ARGs sets, transcriptome files, and clinical data. The "limma" package was then screen differential while also using univariate Cox regression analysis explore prognostic ARGs. "ConsensusClusterPlus" perform aging patterns...