WITHDRAWN: Artificial intelligence in cognitive psychology — Influence of literature based on artificial intelligence on children's mental disorders

Zhang, Xiaoting; Wang, Ruihong; Sharma, Ashutosh; Deverajan, Ganesh Gopal

doi:10.1016/j.avb.2021.101590

Cited by 22 publications

(18 citation statements)

References 22 publications

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“…With the continuous updating of new imaging equipment in clinical medicine, AI has also developed, which provides basic technical support for CT examinations to diagnose cancer [21,23,[39][40][41][42]. Based on AI medical imaging equipment, 120 patients with liver tumors were grouped, blood-rich patients accounted for 53.14%, deposition effect of LCTE was better, blood-poor patients accounted for 25.73%, and deposition effect of LCTE was poor.…”

Section: Discussionmentioning

confidence: 99%

CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging

Liu

Wang

et al. 2021

Mathematical Problems in Engineering

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Artificial intelligence (AI) has made various developments in the image segmentation techniques in the field of medical imaging. This article presents a liver tumor CT image segmentation method based on AI medical imaging-based technology. This study proposed an artificial intelligence-based K-means clustering (KMC) algorithm which is further compared with the region growing (RG) method. In this study, 120 patients with liver tumors in the Post Graduate Institute of Medical Education & Research Hospital, Chandigarh, India, were selected as the research objects, and they were classified according to liver function (Child–Pugh), with 58 cases in grade A and 62 cases in grade B. The experimentation indicates that liver tumor showed low density on plain CT scan, moderate enhancement in the arterial phase of the enhanced scan, and low-density filling defect in the involved blood vessel in the portal venous phase (PVP). It was observed that the CT examination is more sensitive to liver metastasis than hepatocellular carcinoma ( P < 0.05 ). The outcomes obtained depict the good deposition effect of lipiodol chemotherapy emulsion (LCTE) in the contrast group with rich blood type accounted for 53.14% and the patients with the poor blood type accounted for 25.73% showed poor deposition effect. The comparison with the state-of-the-art method reveals that the segmentation effect of the KMC algorithm is better than that of the conventional RG method.

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Section: Discussionmentioning

confidence: 99%

CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging

Liu

Wang

et al. 2021

Mathematical Problems in Engineering

Self Cite

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“…The Web server client includes another Web service, J2EE component, or any Java application. The Web service client view can realize remote, which provides local and remote transparency [39,40]. The online translation system can provide another Web server, filter and disable Web service requests, and provide security constraints and login.…”

Section: Web Service Of Machine Translationmentioning

confidence: 99%

Research on Machine Translation of Deep Neural Network Learning Model Based on Ontology

Tian

Khanna²,

Pljonkin

2021

IJCAI

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To align different ontologies, it is necessary to find effective ways to achieve interoperability of information in the context of the Semantic Web. The development of accurate and reliable techniques to automatically perform this task, it is becoming more and more crucial as overlap between ontologies grows proportionally. In order to solve the problem that traditional machine translation cannot meet the needs of users because of the slow translation speed. According to the characteristics of Ontology's domain knowledge concept system, deep neural network learning model based machine translation method is proposed. Through the experimental design, we examine the translation time and BLEU score and other indicators. After junior translators use the tools, the translation time is reduced by 34.0% and the BLEU score increases by 7.59; after the senior translators use the tools, the translation time is reduced by 11.3%, and the BLEU score is increased by 1.67. Analysis of the experimental results shows that the essence of this method is to complement translation skills, so it is more effective for junior translators who are not good enough in translation skills. The machine translation method based on deep neural network learning can significantly improve the quality and efficiency of translation.Povzetek: Predstavljena je metoda prevajanja s pomočjo globokih nevronskih mrež in ontologij.

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“…After two major delays in AI and HCI, people no longer imagine that computers are capable of surpassing human beings completely, which is impossible under current technical conditions. People turn to study the most practical and achievable issues, leading to the gradual division of AI into five relatively independent disciplines based on random probability model and calculation, namely, cognitive science, natural language understanding, computer vision, machine learning, and robotics (Zhang et al, 2021). AI and HCI are also reflected in the evaluation of psychological changes of college staff.…”

Section: Analysis Of Academic Management and Psychological Characteristics Of Teaching Staff Artificial Intelligence And Human-computer Imentioning

confidence: 99%

The Influence of “Artificial Intelligence + Human–Computer Interaction” on Teachers’ Psychological Changes in Academic Management in Colleges

et al. 2021

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The purpose was to analyze the psychological changes of teaching staff in the academic management of local colleges, and briefly explore the role of teaching staff in the development of the social economy and colleges. In the environment of artificial intelligence and human–computer interaction (HCI), first, the relevant theories of teaching staffs’ psychological status and the characteristics of teaching staff in college academic management were analyzed and expounded. Next, the way of the questionnaire was selected to analyze the psychology of teaching staff in college academic management at different ages, professional titles, academic qualifications, disciplines, and teaching years. The results showed that the mental health level of college teachers was lower than the current national adult standard; the mental health level of female teachers in colleges was higher than that of male teachers; the p value of mental health of college teachers with different ages, professional titles, education, disciplines, and teaching years was greater than 0.05, indicating that there was no significant difference; the p-value of professional academic and mental health was less than 0.01, indicating that there was a significant correlation, that was, teachers’ professional academic exerted a significant impact on teachers’ mental health. In short, under the background of artificial intelligence and HCI’s rapid development, higher education was moving forward with high quality, and more attention should be paid to the psychological changes of college teaching staff.

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WITHDRAWN: Artificial intelligence in cognitive psychology — Influence of literature based on artificial intelligence on children's mental disorders

Cited by 22 publications

References 22 publications

CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging

CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging

Research on Machine Translation of Deep Neural Network Learning Model Based on Ontology

The Influence of “Artificial Intelligence + Human–Computer Interaction” on Teachers’ Psychological Changes in Academic Management in Colleges

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