Learning Methods of Business Intelligence and Group Related Diagnostics on Patient Management by Using Artificial Dynamic System

Hamad, Àbdulsattar Abdullah; Abdulridha, Mustafa Mahdi; Kadhim, Noor Mohammed; Pushparaj, S.; Meenakshi, R.; Ibrahim, Abdelrahman Mohamed

doi:10.1155/2022/4891601

Cited by 17 publications

(5 citation statements)

References 13 publications

(9 reference statements)

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“…Radiology today is a diagnostic and therapeutic support specialty since it includes from conventional radiology to mammography, computed tomography, ultrasound, magnetic resonance, nuclear medicine, positron emission tomography, and radiotherapy [6]. In radiology, technologies have been advancing very fast and are becoming increasingly indispensable in the continuous development of this area.…”

Section: Review Of Literaturementioning

confidence: 99%

[Retracted] Early Diagnosis of Breast Cancer Using Image Processing Techniques

Younis¹,

Ali

Alhafidhb

et al. 2022

Journal of Nanomaterials

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Cancer is a noncommunicable chronic disease that indistinctly affects people of any nationality, race, ethnicity, age, or social class. Because of its unpredictability, receiving the diagnosis of this disease is almost always alarming for the patient. Breast cancer, especially among women, occupies a prominent position in this ranking. However, if diagnosed early, there is an excellent chance of a cure. In this sense, digital technologies have been advancing at an increasingly fast pace to support the early diagnosis of the disease. Clinical analysis of breast cancer is commonly performed using diagnostic imaging. One of the most used exams considered the main one for the early detection of this type of cancer is mammography. This exam allows the visualization of breast tissue from image screening using X-rays. In this sense, the use of computational techniques is essential to assist medical professionals in diagnosing this disease, thus making prevention and early diagnosis even more effective in the current context. The present work is limited to the use of digital technologies (image processing and artificial intelligence) that cooperate with the early diagnosis of breast cancer, which supports the medical professional to analyze images and be able to diagnose, from an early stage, the emergence of breast cancer of the disease, significantly increasing the chances of curing it. It can be gathered from this research how the discovery of X-rays and the growth in this sector combined with cutting-edge technology have benefitted in the early detection of the disease and even offered the cure of many cases.

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Section: Review Of Literaturementioning

confidence: 99%

[Retracted] Early Diagnosis of Breast Cancer Using Image Processing Techniques

Younis¹,

Ali

Alhafidhb

et al. 2022

Journal of Nanomaterials

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“…Evaluation: Determining the accuracy, reliability, and applicability of data and arguments. (Hamad et al, 2022) These kinds of critical thinking abilities can be used in a variety of settings, such as the workplace, the classroom, and personal relationships. They are frequently related to one another.…”

Section: Issn: 2455-6580mentioning

confidence: 99%

The Impact of Integrating Critical Thinking into English Instruction on Pupil’s Academic Achievement

Alaa Sabah Mohammed,

Haneen Abdul Kadhim Abdul Hassan,

Noor Mohammed Kadhim

et al. 2024

The Creative Launcher

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Critical thinking does not mean challenging thinking that does not accept coexistence with others and starts from the “ego” and aims to obliterate the other thought, eliminate it, and replace it. Rather, critical thinking is constructive and calm thinking that recognizes and respects other thoughts and calls for research into different ideas to clarify and benefit them, to improve the existing situation and to increase their effectiveness to achieve the good for all. This paper reports impact of Critical Thinking in English Teaching on Students’ Achievement, the investigator selected an experimental design with two groups one experimental and the other control in order to verify. The researcher intentionally chose the Saqur Qurash school, a group of fifth-grade students in the city of Kut. It was three groups, as the total number of students reached (100) students. The research sample was chosen after they were distributed Randomly among three groups, two groups of (66) students were selected. The investigator prepared teaching plans for those topics, and teaches the two groups and then tested the pupils of the two groups at the end of the experiment. The paper concludes with a summary of the implications of the findings for the future of learning and teaching and recommendations relevant to advancing teaching for critical thinking with children.

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“…Link prediction is the prediction of missing links in the current network and the generation of new links in a future network through the known network structure and other information [ 1 ]. It has a wide range of practical value regarding friend recommendation [ 3 ], product recommendation [ 4 ], knowledge graph completion [ 6 ], and other areas [ 7 , 8 , 9 ].…”

Section: Related Workmentioning

confidence: 99%

Graph Neural Network-Based Efficient Subgraph Embedding Method for Link Prediction in Mobile Edge Computing

Deng

Jun

2023

Sensors

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Link prediction is critical to completing the missing links in a network or to predicting the generation of new links according to current network structure information, which is vital for analyzing the evolution of a network, such as the logical architecture construction of MEC (mobile edge computing) routing links of a 5G/6G access network. Link prediction can provide throughput guidance for MEC and select appropriate c nodes through the MEC routing links of 5G/6G access networks. Traditional link prediction algorithms are always based on node similarity, which needs predefined similarity functions, is highly hypothetical and can only be applied to specific network structures without generality. To solve this problem, this paper proposes a new efficient link prediction algorithm PLAS (predicting links by analysis subgraph) and its GNN (graph neural network) version PLGAT (predicting links by graph attention networks) based on the target node pair subgraph. In order to automatically learn the graph structure characteristics, the algorithm first extracts the h-hop subgraph of the target node pair, and then predicts whether the target node pair will be linked according to the subgraph. Experiments on eleven real datasets show that our proposed link prediction algorithm is suitable for various network structures and is superior to other link prediction algorithms, especially in some 5G MEC Access networks datasets with higher AUC (area under curve) values.

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Learning Methods of Business Intelligence and Group Related Diagnostics on Patient Management by Using Artificial Dynamic System

Cited by 17 publications

References 13 publications

[Retracted] Early Diagnosis of Breast Cancer Using Image Processing Techniques

[Retracted] Early Diagnosis of Breast Cancer Using Image Processing Techniques

The Impact of Integrating Critical Thinking into English Instruction on Pupil’s Academic Achievement

Graph Neural Network-Based Efficient Subgraph Embedding Method for Link Prediction in Mobile Edge Computing

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