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| 1 | Predicting Early Mortality After Acute Variceal Hemorrhage Based on Classification and Regression Tree Analysis显示文摘 | Salvador Augustin Laura Muntaner José T. Altamirano Antonio González Esteban Saperas Joan Dot Monder Abu–Suboh Josep R. Armengol Joan R. Malagelada Rafael Esteban Jaime Guardia Joan Genescà | 2009 | Clinical Gastroenterology and Hepatology2009，，12： | 1 |
| 2 | Performance evaluation and design tradeoffs of on-chip interconnect architectures显示文摘 | BAKHOUYA M SUBOH S GABER J | | 0，，06： | 1 |
| 3 | Predicting Early Mortality After Acute Variceal Hemorrhage Based on Classification and Regression Tree Analysis显示文摘 | Salvador Augustin Laura Muntaner José T. Altamirano Antonio González Esteban Saperas Joan Dot Monder Abu–Suboh Josep R. Armengol Joan R. Malagelada Rafael Esteban Jaime Guardia Joan Genescà | 2009 | Clinical Gastroenterology and Hepatology2009，，12： | 1 |
| 4 | An interconnection architecture for network-on-chip systems显示文摘 | Suboh S Bakhouya M Gaber J | 2008 | Telecommunication Systems2008，37，1： | 1 |
| 5 | Esophageal foreign bodies:a Jordanian experience显示文摘 | Mahafza T Batieha A Suboh M | | 0，，03： | 1 |
| 6 | Esophageal foreign bodies: a Jordanian experience 显示文摘 | Mahafza T Batieha A Suboh M | 2002 | Int J Pediatr Otorhinolaryngol2002，64，3： | 1 |
| 7 | Hyperuricemia Prediction Using Photoplethysmogram and Arteriograph显示文摘Hyperuricemia is an alarming issue that contributes to cardiovascular disease.Uric acid(UA)level was proven to be related to pulse wave velocity,a marker of arterial stiffness.A hyperuricemia prediction method utilizing photoplethysmogram(PPG)and arteriograph by using machine learning(ML)is proposed.From the literature search,there is no available papers found that relates PPG with UA level even though PPG is highly associated with vessel condition.The five phases in this research are data collection,signal preprocessing including denoising and signal quality indexes,features extraction for PPG and SDPPG waveform,statistical analysis for feature selection and classification of UA levels using ML.Adding PPG to the current arteriograph able to reduce cost and increase the prediction performance.PPG and arteriograph data were measured from 113 subjects,and 226 sets of data were collected from the left and right hands of the subjects.The performance of four types of ML,namely,artificial neural network(ANN),linear discriminant analysis(LDA),k-nearest neighbor(kNN),and support vector machine(SVM)in predicting hyperuricemia was compared.From the total of 98 features extracted,16 features of which showed statistical significance for hyper and normouricemia.ANN gives the best performance compared to the other three ML techniques with 91.67%,95.45%,and 94.12%for sensitivity,specificity,and accuracy,respectively.Features from PPG and arteriograph able to be used to predict hyperuricemia accurately and noninvasively.This study is the first to find the relationship of PPG with hyperuricemia.It shows a significant relation between PPG signals and arteriograph data toward the UA level.The proposed method of UA prediction shows its potential for noninvasive preliminary assessment. | Hafifah Ab Hamid Nazrul Anuar Nayan Mohd Zubir Suboh Nurin Izzati Mohamad Azizul Mohamad Nazhan Mohd Nizar Amilia Aminuddin Mohd Shahrir Mohamed Said Saharuddin Ahmad | 2022 | Computers, Materials & Continua2022，，4： | 0 |
| 8 | Cardiovascular Disease Prediction Among the Malaysian Cohort Participants Using Electrocardiogram显示文摘A comprehensive study was conducted to differentiate cardiovascular disease (CVD) subjects from non-CVD subjects using short recording electrocardiogram (ECG) of 244 Malaysian adults in The MalaysianCohort project. An automated peak detection algorithm to detect nine fiducialpoints of electrocardiogram (ECG) was developed. Forty-eight features wereextracted in both time and frequency domains, including statistical featuresobtained from heart rate variability and Poincare plot analysis. These includefive new features derived from spectrum counts of five different frequencyranges. Feature selection was then made based on p-value and correlationmatrix. Selected features were used as input for five classifiers of artificialneural network (ANN), k-nearest neighbors (kNN), support vector machine(SVM), discriminant analysis (DA), and decision tree (DT). Results showedthat six features related to T wave were statistically significant in distinguishingCVD and non-CVD groups. ANN had performed the best with 94.44% specificity and 86.3% accuracy, followed by kNN with 80.56% specificity, 86.49%sensitivity and 83.56% accuracy. The novelties of this study were in providingalternative solutions to detect P-onset, P-offset, T-offset as well as QRS-onsetpoints using discrete wavelet transform method. Additionally, two out of thefive newly proposed spectral features were significant in differentiating bothgroups, at frequency ranges of 1–10 Hz and 5–10 Hz. The prediction outcomeswere also comparable to previous related studies and significantly importantin using ECG to predict cardiac-related events among CVD and non-CVDsubjects in the Malaysian population. | Mohd Zubir Suboh Nazrul Anuar Nayan Noraidatulakma Abdullah Nurul Ain Mhd Yusof Mariatul Akma Hamid Azwa Shawani Kamalul Arinfin Syakila Mohd Abd Daud Mohd Arman Kamaruddin Rosmina Jaafar Rahman Jamal | 2022 | Computers, Materials & Continua2022，，4： | 0 |
| 9 | Trichomonas vaginalis infection in a low-risk women attended in Obstetrics and Gynaecology Clinic, Universiti Kebangsaan Malaysia Medical Centre显示文摘Objective: To investigate the presence of trichomoniasis among women attending the Obstetrics and Gynaecology Clinic, Universiti Kebangsaan Malaysia Medical Centre.Methods: A total of 139 high vaginal swabs were taken from the subjects and sent to the laboratory in Amies gel transport media. The specimens were examined for the presence of Trichomonas vaginalis using wet mount, Giemsa staining and cultured in Diamond's medium. Sociodemographic characteristics and gynaecological complaints were obtained in private using structured questionnaire applied by one investigator.Results: The median age was 32 years, with an interquartile interval of 9.96. Most of the subjects were Malays(76.9%) and the remaining were Chinese(15.1%), Indians(2.2%)and other ethnic groups(5.8%). One hundred and thirty eight(99.3%) of the women were married and 98.6% had less than 6 children. More than half(75.5%) of the women's last child birth was less than 6 years ago. Forty seven percent of them were involved in supporting administrative work and 64.7% of the women gave a history of previous or current vaginal discharge.Conclusions: The present study reported zero incidence rate of trichomoniasis. The low incidence rate was postulated due to all women who participated in this study were categorized into a low-risk group. | Norhayati Moktar Nor Liyana Ismail Phoy Cheng Chun Mohamad Asyrab Sapie Nor Farahin Abdul Kahar Yusof Suboh Noraina Abdul Rahim Nor Azlin Mohamed Ismail Tengku Shahrul Anuar | 2016 | Asian Pacific Journal of Tropical Biomedicine2016，6，8： | 0 |
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