Overview of deep learning-based cell image analysis. A typical analysis pipeline consists of a retraining module and an inference module: the inference module directly produces estimated metrics.
Recent advancements in deep learning have transformed the analysis of blood cell images and the classification of leukemia. By employing complex neural network architectures, such as convolutional ...
A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach ...
Using Early Biomarker Change and Treatment Adherence to Predict Risk of Relapse Among Patients With Chronic Myeloid Leukemia Who Are in Remission The imaging cohort consisted of positron emission ...
Recently, Assoc. Prof. Bo Peng (Northwestern Polytechnical University) and Prof. Lin Li (Xiamen University), et ...
Completed phase 1a dose escalation study of the first oral ENPP1 inhibitor RBS2418 immunotherapy in subjects with metastatic solid tumors. SECN-15: A novel treatment option for patients with ...
Understanding how genes are switched on and off in specific cell types remains one of biology's central challenges. While AI ...
Machine Learning and Single-Cell Technology Combined to Drive High-Performance Cell Line Development
The integrated approach is designed to adapt to the evolving needs of new therapeutic modalities, delivering both speed and performance.
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