From Big Data to Bedside (DB2B): Artificial Intelligence in Precision Oncology
Monday, February 27, 2023
Cancers are genomic diseases caused by somatic genome alterations (SGAs). The cause and disease mechanisms of tumors are highly individualized and heterogeneous, leading to a broad spectrum of molecular, cellular, and clinical phenotypes. Therefore, the treatment of a cancer patient should be individualized based on the disease mechanism of the tumor, i.e., precision oncology. With available big data on cancers, artificial intelligence (AI) will play an indispensable role in transforming genomic, molecular, cellular, and clinical data into knowledge and improving clinical practice. The main utility of AI in precision oncology is twofold: to gain insight of the disease mechanisms of individual tumor (causation) and facilitate clinicians to make optimal clinical decisions (decision). In this presentation, I will discuss our research experience in developing individualized Bayesian causal inference methods to investigate the oncogenic mechanisms, infer the cellular states, model cell-cell communication network, and utilize such mechanism-oriented information to provide clinical decision support, at the level of individual cells, tumors, and patients.
Post Links :
- https://mbzuai-ac-ae.zoom.us/rec/share/PW2KpsRIfTIz00PHRQII
Passcode: pcUR5e&T - https://mbzuai-ac-ae.zoom.us/rec/share/MItzBs4eIgU4RN0yO2Jo629z
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Speaker/s
Dr. Xinghua Lu received his medical training (equivalent to MD) and a Master of Science in Clinical Science from Shangdong Medical University in 1984 and 1988 respectively. He practiced as an attending physician at the Shandong Provincial Hospital for close to a decade before he made a transition to pursue basic medical science. He received his PhD in Pharmacology from the University of Connecticut in 1998 and completed postdoctoral trainings in pharmacology at NIH and the University of Pittsburgh. Since first being exposed to computing in 1985, Dr. Lu has been intrigued by the prospective of computation in biomedicine. In early 2000, he made another career transition to biomedical informatics after receiving formal training as an NLM-sponsored postdoctoral fellow at the University of Pittsburgh. For last two decades, he has been conducting AI in medicine research, with a concentration on precision medicine.
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