Categorization of knowledge graph based recommendation methods and benchmark datasets from the perspectives of application scenarios: A comprehensive survey

Khan, Nasrullah; Ma, Zongmin; Ullah, Aman; Polat, Kemal

doi:10.1016/j.eswa.2022.117737

Cited by 11 publications

(3 citation statements)

References 152 publications

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“…The most striking feature of the study is that it detects BP values for each period by epoching the ECG signal. Research on ECG, PPG, and BP properties is carried out extensively in the literature [ 31 , 33 , 78 ]. Among these signals, QRS and other components exhibited in a heartbeat in the ECG signal, which is the research subject of the study, are generally preferred as feature input [ 27 , 33 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection

Kandaz

Uçar

Polat

et al. 2022

Computational and Mathematical Methods in Medicine

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Objective. Measurement and monitoring of blood pressure are of great importance for preventing diseases such as cardiovascular and stroke caused by hypertension. Therefore, there is a need for advanced artificial intelligence-based systolic and diastolic blood pressure systems with a new technological infrastructure with a noninvasive process. The study is aimed at determining the minimum ECG time required for calculating systolic and diastolic blood pressure based on the Electrocardiography (ECG) signal. Methodology. The study includes ECG recordings of five individuals taken from the IEEE database, measured during daily activity. For the study, each signal was divided into epochs of 2-4-6-8-10-12-14-16-18-20 seconds. Twenty-five features were extracted from each epoched signal. The dimension of the dataset was reduced by using Spearman’s feature selection algorithm. Analysis based on metrics was carried out by applying machine learning algorithms to the obtained dataset. Gaussian process regression exponential (GPR) machine learning algorithm was preferred because it is easy to integrate into embedded systems. Results. The MAPE estimation performance values for diastolic and systolic blood pressure values for 16-second epochs were 2.44 mmHg and 1.92 mmHg, respectively. Conclusion. According to the study results, it is evaluated that systolic and diastolic blood pressure values can be calculated with a high-performance ratio with 16-second ECG signals.

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Section: Discussionmentioning

confidence: 99%

Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection

Kandaz

Uçar

Polat

et al. 2022

Computational and Mathematical Methods in Medicine

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show abstract

“…As a technical system, knowledge map is representative of progress in knowledge engineering in the age of big data [ 23 ]. In recent years, knowledge mapping technology has been widely used in various fields [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 ]. It can show the development and structural relationship of scientific knowledge through graphics and can create the mathematical expression that reveals scientific knowledge and laws to graphical expression.…”

Section: Introductionmentioning

confidence: 99%

Hot Spots and Trends in the Relationship between Cancer and Obesity: A Systematic Review and Knowledge Graph Analysis

Gao

Yang

Xue

et al. 2023

Life

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Cancer is one of the most difficult medical problems in today’s world. There are many factors that induce cancer in humans, and obesity has become an important factor in inducing cancer. This study systematically and quantitatively describes the development trend, current situation and research hotspot of the relationship between cancer and obesity by using document statistics and knowledge graph visualization technology. Through the visualization technology analysis of knowledge graph in this study, the research hotspot and knowledge base source of the relationship between cancer and obesity in the last 20 years have been ascertained. Obesity-related factors, such as immunity, insulin, adiponectin, adipocytokines, nonalcoholic fatty liver and inflammatory reaction, may affect the occurrence of obesity and increase the risk of cancer. Obesity-related cancers include respiratory cancer, colorectal cancer, hepatocellular cancer, prostate cancer, gastric cancer, etc. Our research provides direction and basis for future research in this field, as well as technical and knowledge basis support for experts and researchers in related medical fields.

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“…However, precise and rapid skin lesion segmentation remains challenging due to diversity of skin lesions and the low difference between normal and lesioned skin. In addition, many artifacts such as hair strands and blood vessels cause problems during the segmentation [7][8][9][10][11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach to Skin Lesion Segmentation: Multipath Fusion Model with Fusion Loss

Alhudhaif

Ocal

Barışçı

et al. 2022

Computational and Mathematical Methods in Medicine

Self Cite

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Segmentation of skin lesions plays a very important role in the early detection of skin cancer. However, indistinguishability due to various artifacts such as hair and contrast between normal skin and lesioned skin is an important challenge for specialist dermatologists. Computer-aided diagnostic systems using deep convolutional neural networks are gaining importance in order to cope with difficulties. This study focuses on deep learning-based fusion networks and fusion loss functions. For the automatic segmentation of skin lesions, U-Net (U-Net + ResNet 2D) with 2D residual blocks and 2D volumetric convolutional neural networks were fused for the first time in this study. Also, a new fusion loss function is proposed by combining Dice Loss (DL) and Focal Tversky Loss (FTL) to make the proposed fused model more robust. Of the 2594 image dataset, 20% is reserved for test data and 80% for training data. In test data training, a Jaccard score of 0.837 and a dice score of 0.918 were obtained. The proposed model was also scored on the ISIC 2018 Task 1 test images, whose ground truths were not shared. The proposed model performed well and achieved a Jaccard index of 0.800 and a dice score of 0.880 in the ISIC 2018 Task 1 test set. In addition, it has been observed that the new fused loss function obtained by fusing Focal Tversky Loss and Dice Loss functions in the proposed model increases the robustness of the model in the tests. The proposed new loss function fusion model has outstripped the cutting-edge approaches in the literature.

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Categorization of knowledge graph based recommendation methods and benchmark datasets from the perspectives of application scenarios: A comprehensive survey

Cited by 11 publications

References 152 publications

Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection

Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection

Hot Spots and Trends in the Relationship between Cancer and Obesity: A Systematic Review and Knowledge Graph Analysis

A Novel Approach to Skin Lesion Segmentation: Multipath Fusion Model with Fusion Loss

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