Application of an Artificial Intelligence System Recognition Based on the Deep Neural Network Algorithm

Zhang, Yaru; Zhang, Qian; Yang, Jingxuan

doi:10.1155/2022/4623188

Cited by 3 publications

(1 citation statement)

References 24 publications

(22 reference statements)

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“…Considering the sparseness of the dataset and the size of the storage space, the BIRCH algorithm uses a construction principle similar to that of a B+ tree to read the data compressed in the storage space in one go. By calculating the characteristic distance between sample points, the data set is divided into several categories, and the resulting characteristics show that the Birch algorithm can better handle large-scale data 12 . As can be seen in Figure 5, the text data is divided into four clusters, of which the blue and green clusters are relatively compact and well separated; while the red cluster is partially intersected by the green and blue clusters, which are not well separated and not compact enough; the yellow cluster is not intersected by the other three clusters but is more dispersed.…”

Section: Text Analysismentioning

confidence: 99%

Hotspots and trends of big data research in Chinese medicine based on text mining

Yao

Zhu

et al. 2023

International Conference on Computer Application and Information Security (ICCAIS 2022)

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This paper uses text mining techniques to study the hotspots and trends of Chinese medicine big data research. This study retrieved literature related to “Chinese medicine + big data” from China Knowledge Network and Wan fang database as a collection of research documents. Using python3 and related toolkits, text mining was performed on the relevant literature. Through cluster analysis, we obtained the rules of medication and the construction of big data platforms for Chinese medicine, which have been the hotspots of research in recent years; using co-occurrence analysis, knowledge graph analysis and other big data-related techniques to study the rules of medication, the rules of formulae, the thinking on the application of big data in Chinese medicine, the current situation and the construction of platforms, which are still the future research trends. The use of text mining technology can provide an intuitive and systematic representation of current hotspots as well as future development trends, and can provide methodological summaries and ideas for the modernization and development of Chinese medicine.

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Section: Text Analysismentioning

confidence: 99%

Hotspots and trends of big data research in Chinese medicine based on text mining

Yao

Zhu

et al. 2023

International Conference on Computer Application and Information Security (ICCAIS 2022)

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Neural network models based on clinical characteristics for predicting immunotherapy efficacy in small cell lung cancer

Li,

Chen,

et al. 2024

Malignancy Spectrum

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BackgroundImmunotherapy combined with chemotherapy has been approved as first‐line therapy for small cell lung cancer (SCLC) due to the survival benefit in randomized controlled trials. However, predicting its efficacy remains a challenge in the absence of currently available biomarkers.MethodsA total of 140 individuals with SCLC who received immunotherapy were evaluated retrospectively. These patients were split into two distinct cohorts, the discovery cohort (80% of the total, n = 112) and the validation cohort (20% of the total, n = 28). The objective response rate (ORR), disease control rate (DCR), and responder (progression‐free survival [PFS] > 6 months) were all predicted using neural networks.ResultsWe developed predictive models for three clinical outcomes. ORR scored 0.8964 area under the receiver operating characteristic curve (AUC) in the discovery cohort and 0.8421 AUC in the validation cohort. DCR model had AUC of 0.8618 in the discovery cohort and AUC of 0.7396 in the validation cohort. The responder model had AUC of 0.8116 in the discovery cohort and AUC of 0.7041 in the validation cohort. The models were then compressed into a doctor‐friendly tool.ConclusionThese neural network‐based models, which are based on routine clinical characteristics, accurately predict the efficacy of immunotherapy in patients with SCLC, particularly in terms of ORR.

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A novel driver emotion recognition system based on deep ensemble classification

Zaman

Sun

Shah

et al. 2023

Complex Intell. Syst.

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Driver emotion classification is an important topic that can raise awareness of driving habits because many drivers are overconfident and unaware of their bad driving habits. Drivers will acquire insight into their poor driving behaviors and be better able to avoid future accidents if their behavior is automatically identified. In this paper, we use different models such as convolutional neural networks, recurrent neural networks, and multi-layer perceptron classification models to construct an ensemble convolutional neural network-based enhanced driver facial expression recognition model. First, the faces of the drivers are discovered using the faster region-based convolutional neural network (R-CNN) model, which can recognize faces in real-time and offline video reliably and effectively. The feature-fusing technique is utilized to integrate the features extracted from three CNN models, and the fused features are then used to train the suggested ensemble classification model. To increase the accuracy and efficiency of face detection, a new convolutional neural network block (InceptionV3) replaces the improved Faster R-CNN feature-learning block. To evaluate the proposed face detection and driver facial expression recognition (DFER) datasets, we achieved an accuracy of 98.01%, 99.53%, 99.27%, 96.81%, and 99.90% on the JAFFE, CK+, FER-2013, AffectNet, and custom-developed datasets, respectively. The custom-developed dataset has been recorded as the best among all under the simulation environment.

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Application of an Artificial Intelligence System Recognition Based on the Deep Neural Network Algorithm

Cited by 3 publications

References 24 publications

Hotspots and trends of big data research in Chinese medicine based on text mining

Hotspots and trends of big data research in Chinese medicine based on text mining

Neural network models based on clinical characteristics for predicting immunotherapy efficacy in small cell lung cancer

A novel driver emotion recognition system based on deep ensemble classification

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