Biochimica et biophysica acta. Reviews on cancer
Apr 10, 2021
This review captures some key lessons learned in the course of helping some of America's leading healthcare AI innovators achieve scale and sustained impact in complex research and care delivery ecosystems. AI innovators may find it useful to access ...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 8, 2021
There is often a limited amount of omics data to design predictive models in biomedicine. Knowing that these omics data come from underlying processes that may share common pathways and disease mechanisms, it may be beneficial for designing a more ac...
BACKGROUND: The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development and tumourigenesis. However, methods for translating these high-level concepts into data-le...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 6, 2021
Survival analysis is a popular branch of statistics. At present, many algorithms (like traditional multi-tasking learning model) cannot be applied well in practice because of censored data. Although using some model (like parametric regression model)...
Deregulation of the protein secretory pathway (PSP) is linked to many hallmarks of cancer, such as promoting tissue invasion and modulating cell-cell signaling. The collection of secreted proteins processed by the PSP, known as the secretome, is ofte...
BMC medical informatics and decision making
Apr 3, 2021
BACKGROUND: Artificial intelligence (AI) research is highly dependent on the nature of the data available. With the steady increase of AI applications in the medical field, the demand for quality medical data is increasing significantly. We here desc...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Mar 26, 2021
OBJECTIVES: While the prevalence of active cancer patients experiencing acute stroke is increasing, the effects of active cancer on reperfusion therapy outcomes are inconclusive. Thus, we aimed to compare the safety and outcomes of reperfusion therap...
Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which use...
Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outc...
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