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人工智能(Artificial Intelligence,AI)的蓬勃兴起为现代社会带来了前所未有的机遇,中医药是中华民族传承千年的文化瑰宝。随着人工智能技术不断在中医药领域的科技创新中崭露头角,二者的融合不断加深,人工智能在中医药领域的发展前景、争议挑战也引发了诸多思考。本文将从人工智能在中医药领域的应用入手,对人工智能辅助中医诊断、智能决策与数据挖掘、健康管理及中草药现代化研究等方面,就近年来国内外研究进展进行总结与分析,以期为AI视域下实现中医药现代化、智能化赋能。  相似文献   
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Purpose

Endovascular treatment with mechanical thrombectomy devices demonstrated high recanalization rates but functional outcome did not correlate with high rates of recanalization obtained. Patient selection prior to the endovascular treatment is very important in the final outcome of the patient. The primary aim of our study was to evaluate the prognostic value of posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) and Pons-Midbrain Index (PMI) scores in patients with Basilar Artery Occlusion (BAO) treated with successful angiographic recanalization after mechanical thrombectomy.

Methods

Retrospective single-center study including 18 patients between 2008 and 2013 who had acute basilar artery occlusion managed with endovascular treatment within 24 hours from symptoms onset and with successful angiographic recanalization. The patients were initially classified into two groups according to clinical outcome and mortality at 90 days. For analysis we also divided patients into groups based on pc-ASPECTS (≥8vs.< 8) and PMI (≥3vs.< 3) on non-contrast CT (NCCT) and CT Angiography Source Images (CTASI). Imaging data were correlated to clinical outcome and mortality rate.

Results

CTASI pc-ASPECTS, dichotomized at < 8 versus≥8, was associated with a favorable outcome (RR: 2.6; 95% CI: 1.3-5.2) and a reduced risk of death (RR: 6.5: 95% CI: 7.8-23.3). All patients that survived and were functionally independent had pc-ASPECTS score≥8. None of the 5 patients with CTASI pc-ASPECTS score less than 8 survived.

Conclusion

PC-ASPECTS on CTASI is helpful for predicting functional outcome after BAO recanalization with endovascular treatment. These results should be validated in a randomized controlled trial in order to decide whether or not to treat a patient with BAO.  相似文献   
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Bipolar disorder (BD) is a common psychiatric mood disorder affecting more than 1-2% of the general population of different European countries. Unfortunately, there is no objective laboratory-based test to aid BD diagnosis or monitor its progression, and little is known about the molecular basis of BD. Here, we performed a comparative proteomic study to identify differentially expressed plasma proteins in various BD mood states (depressed BD, manic BD, and euthymic BD) relative to healthy controls. A total of 10 euthymic BD, 20 depressed BD, 15 manic BD, and 20 demographically matched healthy control subjects were recruited. Seven high-abundance proteins were immunodepleted in plasma samples from the 4 experimental groups, which were then subjected to proteome-wide expression profiling by two-dimensional electrophoresis and matrix-assisted laser desorption/ionization-time-of-flight/time-of-flight tandem mass spectrometry. Proteomic results were validated by immunoblotting and bioinformatically analyzed using MetaCore. From a total of 32 proteins identified with 1.5-fold changes in expression compared with healthy controls, 16 proteins were perturbed in BD independent of mood state, while 16 proteins were specifically associated with particular BD mood states. Two mood-independent differential proteins, apolipoprotein (Apo) A1 and Apo L1, suggest that BD pathophysiology may be associated with early perturbations in lipid metabolism. Moreover, down-regulation of one mood-dependent protein, carbonic anhydrase 1 (CA-1), suggests it may be involved in the pathophysiology of depressive episodes in BD. Thus, BD pathophysiology may be associated with early perturbations in lipid metabolism that are independent of mood state, while CA-1 may be involved in the pathophysiology of depressive episodes.  相似文献   
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目的以基因表达数据集资料为研究对象,分析BCAN基因在肾透明细胞癌中的表达情况以及对患者预后的影响。方法在Oncomine数据库中挖掘BCAN在肾透明细胞癌(ccRCC)中的表达情况。从TCGA数据库中获取ccRCC患者临床资料和目的基因的表达信息并进行统计分析。利用GEO数据库中GSE73731数据集的ccRCC样本进行基因富集分析。利用String数据库分析与BCAN相关的蛋白。结果BCAN低表达组的ccRCC患者在病理分期及T分期方面低于高表达组(P<0.001;P=0.001);N分期及M分期差异无统计学意义(P>0.05)。BCAN低表达组患者的总生存期优于高表达组(P=0.033)。BCAN基因高表达组的样本主要富集在KRAS信号通路。结论BCAN可以通过多种途径来促进肿瘤细胞的侵袭能力,有望成为ccRCC不良预后的重要生物标志物之一。  相似文献   
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