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 ...
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 ...
A team of researchers at the Georgia Institute of Technology and Emory University has developed a deep-ultraviolet (UV) ...
Researchers have unveiled CREsted, a comprehensive software powerhouse. CREsted doesn’t just describe how DNA works; it allows scientists to design entirely new, synthetic enhancers—short DNA ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results