ABSTRACT
Artificial intelligence (AI) is a general term that refers to the use of a machine to imitate intelligent behavior for performing complex tasks with minimal human intervention, such as machine learning; this technology is revolutionizing and reshaping medicine. AI has considerable potential to perfect health-care systems in areas such as diagnostics, risk analysis, health information administration, lifestyle supervision, and virtual health assistance. In terms of immunotherapy, AI has been applied to the prediction of immunotherapy responses based on immune signatures, medical imaging and histological analysis. These features could also be highly useful in the management of cancer immunotherapy given their ever-increasing performance in improving diagnostic accuracy, optimizing treatment planning, predicting outcomes of care and reducing human resource costs. In this review, we present the details of AI and the current progression and state of the art in employing AI for cancer immunotherapy. Furthermore, we discuss the challenges, opportunities and corresponding strategies in applying the technology for widespread clinical deployment. Finally, we summarize the impact of AI on cancer immunotherapy and provide our perspectives about underlying applications of AI in the future.
ABSTRACT
OBJECTIVE@#To explore the association of VEGFR2 gene polymorphisms (rs2305948 and rs1870377) with the effect of levodopa (L-dopa) and dyskinesia in Chinese population and to provide theoretical basis for clinical treatment. @*METHODS@#By using Taqman MGB analysis and gene sequencing, the rs2305948 and rs1870377 polymorphisms of 69 enrolled Parkinson's disease (PD) patients were detected. Among them, 32 cases developed dyskinesia during 5 years and 37 cases did not develop dyskinesia during 8 years (as the control). @*RESULTS@#There was no significant association between the occurrence of dyskinesia and VEGFR2 polymorphisms at rs2305948 and rs1870377. However, rs1870377 polymorphism of AA showed greater maximum L-dopa dose [(565.00±163.55) mg/d vs (396.88±200.39) mg/d, (300.00±80.18) mg/d, P=0.038] and higher value of Modified Abnormal Involuntary Movement Scale (mAIMS) compared with that with polymorphisms of AT and TT [17.00±5.24 vs 8.94±6.53, 7.86±4.45, P=0.026]. @*CONCLUSION@#VEGFR2 genes polymorphism (rs1870377) is associated with maximum L-dopa dose and mAIMS value in PD patients.