Extracting valuable information frombiomedical texts is one of the current research hotspots of concern to a wide range of *** biomedical corpus contains numerous complex long sentences and overlapping relational trip...
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Extracting valuable information frombiomedical texts is one of the current research hotspots of concern to a wide range of *** biomedical corpus contains numerous complex long sentences and overlapping relational triples,making most generalized domain joint modeling methods difficult to apply effectively in this *** a complex semantic environment in biomedical texts,in this paper,we propose a novel perspective to perform joint entity and relation extraction;existing studies divide the relation triples into several steps or ***,the three elements in the relation triples are interdependent and inseparable,so we regard joint extraction as a tripartite classification *** the same time,fromthe perspective of triple classification,we design amulti-granularity 2D convolution to refine the word pair table and better utilize the dependencies between biomedical word ***,we use a biaffine predictor to assist in predicting the labels of word pairs for relation *** model(MCTPL)Multi-granularity Convolutional Tokens Pairs of Labeling better utilizes the elements of triples and improves the ability to extract overlapping triples compared to previous ***,we evaluated our model on two publicly accessible *** experimental results show that our model’s ability to extract relation triples on the CPI dataset improves the F1 score by 2.34%compared to the current optimal *** the DDI dataset,the F1 value improves the F1 value by 1.68%compared to the current optimal *** model achieved state-of-the-art performance compared to other baseline models in biomedical text entity relation extraction.
Artificial Intelligence, including machine learning and deep convolutional neural networks (DCNNs), relies on complex algorithms and neural networks to process and analyze data. DCNNs for visual recognition often requ...
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Road safety is a critical concern worldwide, with millions of lives lost and countless injuries sustained in traffic accidents annually. To address this pressing issue, a costeffective and reliable solution is propose...
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The occurrence of epileptic photosensitivity (Seizures triggered by rapid visual stimuli) has been steadily increasing since the rise of various video platforms. While there are invasive surgical solutions, noninvasiv...
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As the self-driving technology is getting mature for public transportation applications, the safety concern of onboard passengers has become an important issue. It is essential to identify inappropriate or hazardous b...
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Alzheimer’s disease(AD)is a kind of progressive dementia that is frequently accompanied by brain *** the use of the morpho-logical characteristics of MRI brain scans,this paper proposed a method for diagnosing modera...
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Alzheimer’s disease(AD)is a kind of progressive dementia that is frequently accompanied by brain *** the use of the morpho-logical characteristics of MRI brain scans,this paper proposed a method for diagnosing moderate cognitive impairment(MCI)and *** anatom-ical features of 818 subjects were calculated using the FreeSurfer software,and the data were taken from the ADNI *** features were first removed from the dataset after being preprocessed with an age correction algorithm using linear regression to estimate the effects of normal *** these preprocessed characteristics,the extreme learning machine served as a classifier for the diagnosis of AD and *** determining accuracy,sensitivity,specificity,and area under the curve,ten-fold cross validation was *** accuracy of AD diagnosis was 87.62 percent on average after 100 runs,while the area under curve was 94.25 *** sensitivity of the MCI diagnosis was 83.88 percent,while the accuracy was 73.38 *** age correction can help diagnose MCI more *** outcomes showed that the proposed strategy for diagnosing AD and MCI was more effective than existing methods.
Time difference of arrival (TDOA) positioning results obtained using commonly adopted algebraic methods lack uncertainty information. In this letter, we propose to incorporate interval computation into TDOA-based hype...
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Graphics processing units (GPUs) have been increasingly used to solve a range of compute-intensive and data-parallel scientific computing problems that can be perfectly parallelized for performance speedups. Particula...
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Pisciculture encounters an array of intricate challenges that span disease management, preservation of water quality, prevention of genetic hybridization, ensuring the integrity of net systems, sourcing sustainable aq...
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Integrated sensing and communications (ISAC) has emerged as a promising solution for addressing spectrum congestion in sixth-generation communication systems. In this work, we consider the deployment of ISAC in a full...
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