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692 |
Harapan H., Fajar J.K., Supriono S., Soegiarto G., Wulandari L., Seratin F., Prayudi N.G., Dewi D.P., Monica Elsina M.T., Atamou L., Wiranata S., Aprianto D.P., Friska E., Sari Firdaus D.F., Alaidin M., Wardhani F.A., Husnah M., Hidayati N.W., Hendriyanti Y., Wardani K., Evatta A., Manugan R.A., Pradipto W., Rahmawati A., Tamara F., Mahendra A.I., Nainu F., Santoso B., Irawan Primasatya C.A., Tjionganata N., Budiman H.A. |
55844857500;56156139600;57218591523;57193717004;52464692000;57291538600;57291762600;57291994900;57291762700;57292451200;57220591122;57292451300;57291762800;57292675300;57291538700;57291315100;57194724156;57291315200;57292218900;57292909500;57292451400;57292219000;57292219100;57292675400;57192950403;57202301766;57120069200;57291762900;57291995000;57291538800;57291763000; |
The prevalence, predictors and outcomes of acute liver injury among patients with COVID-19: A systematic review and meta-analysis |
2021 |
Reviews in Medical Virology |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116888408&doi=10.1002%2frmv.2304&partnerID=40&md5=8da649362695a47bd93802e3d5061df1 |
Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Department of Internal Medicine, Division of Gastro-Entero-Hepatology, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Department of Internal Medicine, Division of Allergy & Immunology, Universitas Airlangga, Surabaya, Indonesia; Department of Pulmonology and Respiratory Medicine, Universitas Airlangga, Surabaya, Indonesia; Department of Paediatric, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia; Department of Urology, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Faculty of Public Health, Universitas Indonesia, Depok, Indonesia; Faculty of Nursing, Universitas Indonesia, Depok, Indonesia; Faculty of Medicine, Universitas Udayana, Denpasar, Indonesia; Faculty of Medicine, Universitas Indonesia, Depok, Indonesia; Department of Nursing, Faculty of Medicine, Universitas Diponegoro, Semarang, Indonesia; Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia; Master Program of Biology, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, Indonesia; Faculty of Pharmacy, Hasanuddin University, Makassar, Indonesia; Department of Internal Medicine, RSUD Bangil, Pasuruan, Indonesia; Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia; Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia |
Harapan, H., Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia, Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia, Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Fajar, J.K., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Supriono, S., Department of Internal Medicine, Division of Gastro-Entero-Hepatology, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Soegiarto, G., Department of Internal Medicine, Division of Allergy & Immunology, Universitas Airlangga, Surabaya, Indonesia; Wulandari, L., Department of Pulmonology and Respiratory Medicine, Universitas Airlangga, Surabaya, Indonesia; Seratin, F., Department of Paediatric, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia; Prayudi, N.G., Department of Urology, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Dewi, D.P., Faculty of Public Health, Universitas Indonesia, Depok, Indonesia; Monica Elsina, M.T., Faculty of Nursing, Universitas Indonesia, Depok, Indonesia; Atamou, L., Faculty of Nursing, Universitas Indonesia, Depok, Indonesia; Wiranata, S., Faculty of Medicine, Universitas Udayana, Denpasar, Indonesia; Aprianto, D.P., Faculty of Public Health, Universitas Indonesia, Depok, Indonesia; Friska, E., Faculty of Medicine, Universitas Indonesia, Depok, Indonesia; Sari Firdaus, D.F., Faculty of Medicine, Universitas Indonesia, Depok, Indonesia; Alaidin, M., Department of Nursing, Faculty of Medicine, Universitas Diponegoro, Semarang, Indonesia; Wardhani, F.A., Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia; Husnah, M., Master Program of Biology, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, Indonesia; Hidayati, N.W., Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia; Hendriyanti, Y., Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia; Wardani, K., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Evatta, A., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Manugan, R.A., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Pradipto, W., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Rahmawati, A., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Tamara, F., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Mahendra, A.I., Brawijaya Internal Medicine Research Centre, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Nainu, F., Faculty of Pharmacy, Hasanuddin University, Makassar, Indonesia; Santoso, B., Department of Internal Medicine, RSUD Bangil, Pasuruan, Indonesia; Irawan Primasatya, C.A., Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia; Tjionganata, N., Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia; Budiman, H.A., Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia |
The data on the predictors and prognosis of acute liver injury (ALI) among patients in coronavirus disease 2019 (COVID-19) patients are limited. The aim of this study was to determine the prevalence, predictors and outcomes of ALI among patients with COVID-19. A systematic review was conducted up to 10 June 2021. The relevant papers were searched from PubMed, Embase, Cochrane and Web of Science, and the data were analysed using a Z test. A total of 1331 papers were identified and 16 papers consisting of 1254 COVID-19 with ALI and 4999 COVID-19 without ALI were analysed. The cumulative prevalence of ALI among patients with COVID-19 was 22.8%. Male and having low lymphocyte levels were more likely to be associated with ALI compared with female and having higher lymphocyte level, odds ratio (OR): 2.70; 95% confidence interval (CI): 2.03, 3.60 and mean difference (MD) −125; 95% CI: −207, −43, respectively. COVID-19 patients with ALI had higher risk of developing severe COVID-19 compared with those without ALI (OR: 3.61; 95% CI: 2.60, 5.02). Our findings may serve as the additional evaluation for the management of ALI in COVID-19 patients. © 2021 John Wiley & Sons Ltd. |
acute liver injury; COVID-19; outcome; predictor; prevalence |
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John Wiley and Sons Ltd |
10529276 |
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Review |
Q1 |
2060 |
1246 |
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No records
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117 |
Umiatin, Indrasari W., Taryudi, Sari P., Mazfufah N.F., Rosadi I. |
57202292099;56069603500;57003576500;55776482300;57215595521;57204720098; |
Effect of pulse electromagnetic field exposure on the expression of lipo protein lipase (LPL) on the differentiation of mesenchymal stem cell |
2021 |
Journal of Physics: Conference Series |
2019 |
1 |
012107 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119203085&doi=10.1088%2f1742-6596%2f2019%2f1%2f012107&partnerID=40&md5=cd764de9d9b9c1287f97fb09cfd8eea2 |
Department of Physics, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta, Indonesia; Department of Electronic Engineering, Faculty of Engineering, Universitas Negeri Jakarta, Indonesia; Department of Biology, Faculty of Medicine, Universitas Indonesia, Indonesia, Jl. Rawamangun Muka, Jakarta, 13220, Indonesia; Stem Cells and Tissue Engineering Research Center, IMERI, Faculty of Medicine, Universitas Indonesia, Indonesia; Department of Biology, Faculty of Mathematics and Natural Sciences, Mulawarman University, Samarinda, Indonesia |
Umiatin, Department of Physics, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta, Indonesia; Indrasari, W., Department of Physics, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta, Indonesia; Taryudi, Department of Electronic Engineering, Faculty of Engineering, Universitas Negeri Jakarta, Indonesia; Sari, P., Department of Biology, Faculty of Medicine, Universitas Indonesia, Indonesia, Jl. Rawamangun Muka, Jakarta, 13220, Indonesia; Mazfufah, N.F., Stem Cells and Tissue Engineering Research Center, IMERI, Faculty of Medicine, Universitas Indonesia, Indonesia; Rosadi, I., Department of Biology, Faculty of Mathematics and Natural Sciences, Mulawarman University, Samarinda, Indonesia |
Pulsed electromagnetic fields (PEMFs) have an important role in cell differentiation. Previous study reported that PEMFs had positive and negative effect towards cell differentiation that depends on their frequencies applied to the cells. Human adipose-derived stem cells (ASCs) are mesenchymal stem cells that have an ability to differentiate into several types of cell including adipocytes, chondrocytes and osteocytes. This study aimed to evaluate the effect of human ASCs towards their adipogenic differentiation during PEMFs exposure. Human ASCs were isolated from adipose tissue. The cells then cultured in specific medium of adipocyte that induced ASCs differentiation along with PEMFs exposure. The maximum magnetic field used is 2 mT with a frequency of 75 Hz. To confirm the effect of PEMFs exposure towards adipogenic differentiation, mRNA expression of lipo protein lipase (LPL) was measured in mRNA expression level. The results showed that ASCs cultured on adipogenic differentiation without PEMFs exposure gradually increased LPL expression until day 14 of observation, while ASCs with PEMFs exposure significantly decreased LPL expression from day 2 to day 14. Based on the results, we concluded that PEMFs exposure can inhibit LPL expression that suppressed adipogenic differentiation. © 2021 Institute of Physics Publishing. All rights reserved. |
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Electromagnetic field effects; Electromagnetic fields; Proteins; Stem cells; Adipogenic differentiations; Adipose derived stem cells; Cell differentiation; Cell-be; Cell/B.E; Electromagnetic field exposure; Human adipose; Lipo proteins; Mesenchymal stem cell; Pulsed electromagnetic fields; Cell culture |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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280 |
Pradita L.W., Kamilla D.N., Soedarsono N., Yunaini L., Auerkari E.I. |
57226576844;57226575340;14049161500;57192911515;10139113000; |
Intron 4 VNTR A/B polymorphism of endothelial nitric oxide synthase gene in periodontitis |
2021 |
Journal of Physics: Conference Series |
1943 |
1 |
012087 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112023901&doi=10.1088%2f1742-6596%2f1943%2f1%2f012087&partnerID=40&md5=a0fb2d74d58911990f7e8f70aaf919b9 |
Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Department of Medical Biology, Faculty of Medicine, University of Indonesia, Jakarta, Indonesia |
Pradita, L.W., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Kamilla, D.N., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Soedarsono, N., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Yunaini, L., Department of Medical Biology, Faculty of Medicine, University of Indonesia, Jakarta, Indonesia; Auerkari, E.I., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia |
Nitric Oxide (NO) is an important mediator in the inflammatory and immune systems. The eNOS gene is one of the three isoforms of Nitric Oxide Synthase (NOS), which is responsible for synthesizing NO. Periodontitis is an inflammatory disease in periodontal tissue with genetic involvement. Polymorphism in eNOS gene changes the functional aspect of this gene and is associated with several inflammatory diseases including periodontitis. Aim: To detect Endothelial Nitric Oxide Synthase intron 4 gene polymorphism in Indonesian population with periodontitis. Analysis of the Endothelial Nitric Oxide Synthase (eNOS) intron 4 gene polymorphism was observed by carrying out PCR method followed by electrophoresis for the analysis, without the usage of restriction enzyme. The chi-square test and odds ratio were performed for statistical analysis. In this study, there were 34 samples with AA genotype, 3 samples with AB genotype, and 13 samples with BB genotype in periodontitis group. Whereas in the control group, there were 41 samples with AA genotype and 9 samples with BB genotype. AB genotype was absent in the control group. In periodontitis group, there were 71 A alleles and 29 B alleles, and in the control group, 82 A alleles and 18 B alleles were found. Polymorphic genotypes and alleles were found higher in periodontitis sample (32% and 29%) than healthy controls (18%). The polymorphism of eNOS intron 4 was found in periodontitis patients. There is no significant distribution difference was found between the periodontitis patients and the control group. ENOS intron 4 gene polymorphism does not affect the risk of periodontitis. © Published under licence by IOP Publishing Ltd. |
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Electrophoresis; Genes; Nitric oxide; Polymerase chain reaction; Polymorphism; Statistical tests; Endothelial nitric oxide synthase; Endothelial nitric-oxide synthase (eNOS); Functional aspects; Gene polymorphism; Inflammatory disease; Nitric-oxide synthase; Periodontal tissue; Restriction enzymes; Diseases |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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281 |
Gani A.Z., Zahra P.K., Soedarsono N., Yunaini L., Auerkari E.I. |
57222626782;57226565453;14049161500;57192911515;10139113000; |
Vitamin D receptor TaqI (rs731236) gene polymorphism in caries patients |
2021 |
Journal of Physics: Conference Series |
1943 |
1 |
012093 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112014710&doi=10.1088%2f1742-6596%2f1943%2f1%2f012093&partnerID=40&md5=5891ab3c26dbd9bd14c0be24643600b3 |
Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Department of Medical Biology, Faculty of Medicine, University of Indonesia, Jakarta, Indonesia |
Gani, A.Z., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Zahra, P.K., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Soedarsono, N., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia; Yunaini, L., Department of Medical Biology, Faculty of Medicine, University of Indonesia, Jakarta, Indonesia; Auerkari, E.I., Department of Oral Biology, Faculty of Dentistry, University of Indonesia, Jakarta, Indonesia |
Vitamin D receptor (VDR) is included in the type of protein that serves as the biological function regulator of vitamin D. Tooth formation, especially in enamel and dentin calcification, as well as maintaining the balance of phosphate and calcium ions which is an important factor in protecting teeth requires support from vitamin D. The VDR gene will regulate the activity of VDR proteins. Caries is a multifactorial disease in which genetic factors can affect the host susceptibility to caries. Polymorphism in the VDR gene is suspected to affect the host susceptibility to caries through changes in calcium metabolism. This study aims to discover the VDR gene polymorphism and its association with caries patients in Indonesia. 100 DNA samples from 100 blood samples, including 50 dental caries patients and 50 healthy controls, were analyzed using PCR-RFLP technique. PCR products were digested with the TaqI restrictive enzyme, then assessed with statistical analysis using Fisher's exact test and Continuity correction test. In the caries group, there were no samples with CC genotype, 4 samples with CT genotype, and 46 samples with TT genotype. There were also 4 C alleles and 96 T alleles. Polymorphic genotypes and alleles were found higher in the caries group (100% and 96%) than healthy controls (88% and 84%). These results conclude that the polymorphism of VDR TaqI (rs731236) gene was found in patients with dental caries. The distribution of genotypes and allele distributions of VDR TaqI (rs731236) gene between caries and healthy controls significantly differs noticeable (p <0.05). © Published under licence by IOP Publishing Ltd. |
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Biomineralization; Calcium; Polymerase chain reaction; Polymorphism; Proteins; Vitamins; Biological functions; Calcium metabolism; Continuity corrections; Gene polymorphism; Healthy controls; Host susceptibility; Multifactorial disease; Vitamin D receptor; Genes |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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492 |
Maulidina F., Rustam Z., Hartini S., Wibowo V.V.P., Wirasati I., Sadewo W. |
57221906584;26422482100;57211529061;57221911837;57221806240;55014544900; |
Feature optimization using Backward Elimination and Support Vector Machines (SVM) algorithm for diabetes classification |
2021 |
Journal of Physics: Conference Series |
1821 |
1 |
012006 |
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1 |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103897338&doi=10.1088%2f1742-6596%2f1821%2f1%2f012006&partnerID=40&md5=26c4c2f598bd765549c0283978c63185 |
Departement of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Department of Neurosurgery, Faculty of Medicine, University of Indonesia, Dr. Cipto Mangunkusumo National General Hospital, Indonesia |
Maulidina, F., Departement of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Rustam, Z., Departement of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Hartini, S., Departement of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Wibowo, V.V.P., Departement of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Wirasati, I., Departement of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Sadewo, W., Department of Neurosurgery, Faculty of Medicine, University of Indonesia, Dr. Cipto Mangunkusumo National General Hospital, Indonesia |
Diabetes is a disease that occurs when the blood glucose level is higher than normal and also leads to health problems. Early and accurate diagnosis needs to be carried out on individuals affected by this disease. Furthermore, excellent treatment needs to be provided to prevent worse situations. Some studies have used several machine learning methods to diagnose diabetes. Furthermore, in this study, the Backward Elimination and Support Vector Machine (SVM) algorithm was used to classify the PIMA Indians diabetes dataset. It consisted of 268 diabetic and 500 non-diabetic patients with eight attributes. Backward Elimination is a feature selection method used to remove irrelevant features based on the linear regression model. Using this method, the right features for the model was expected. This method has some advantages which include increasing training time, decreasing complexity and improving performance and accuracy. Therefore, the performance of SVM improved. Based on the experiments, it was discovered that by combining feature selection algorithm (backward elimination) and SVM, the highest accuracy obtained was 85.71% using 90% data training. Therefore, it was concluded that Backward Elimination combined with SVM algorithm is an excellent method to classify diabetes by using the PIMA Indians diabetes dataset. © Published under licence by IOP Publishing Ltd. |
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Classification (of information); Diagnosis; Experimental mineralogy; Feature extraction; Learning systems; Regression analysis; Feature optimizations; Feature selection algorithm; Feature selection methods; Improving performance; Linear regression models; Machine learning methods; Support vector machine algorithm; Support vector machines algorithms; Support vector machines |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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493 |
Wibowo V.V.P., Rustam Z., Hartini S., Maulidina F., Wirasati I., Sadewo W. |
57221911837;26422482100;57211529061;57221906584;57221806240;55014544900; |
Ovarian cancer classification using K-Nearest Neighbor and Support Vector Machine |
2021 |
Journal of Physics: Conference Series |
1821 |
1 |
012007 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103891589&doi=10.1088%2f1742-6596%2f1821%2f1%2f012007&partnerID=40&md5=8b428e7f3e510029f71b6c464cefbd2d |
Department of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Department of Neurosurgery, Faculty of Medicine, University of Indonesia, Dr. Cipto Mangunkusumo National General Hospital, Indonesia |
Wibowo, V.V.P., Department of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Rustam, Z., Department of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Hartini, S., Department of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Maulidina, F., Department of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Wirasati, I., Department of Mathematics, University of Indonesia, Depok, 16424, Indonesia; Sadewo, W., Department of Neurosurgery, Faculty of Medicine, University of Indonesia, Dr. Cipto Mangunkusumo National General Hospital, Indonesia |
Ovarian cancer is one of the common malignancies in women and a known cause of death. This condition occurs when a tumor appears from the growth of abnormal cells in the ovary. It causes about 140.000 deaths out of 225.000 cases annually. Most women with ovarian cancer do not have distinctive signs and symptoms even at the late stage. Therefore, diagnosis at an early stage is necessary because it has a significant impact on the survival rate. Machine learning with various methods can be used in the medical field to classify diseases. Among the many methods, K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) were used and analyzed in this study to classify ovarian cancer. The data used were from Al Islam Bandung Hospital consisting of 203 instances with 130 labeled ovarian cancer and 73 as non-ovarian. The results showed that the KNN produced higher results than SVM with 90.47% of accuracy and 94.11% of F1-score, while SVM produced accuracy and F1-score values of 90.47% and 92.30% respectively. © Published under licence by IOP Publishing Ltd. |
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Diagnosis; Diseases; Motion compensation; Nearest neighbor search; F1 scores; K nearest neighbor (KNN); K-nearest neighbors; Late stage; Medical fields; Ovarian cancers; Survival rate; Support vector machines |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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518 |
Apriadi W., Gani H.S., Prayitno P., Ibrahim N., Wijaya S.K. |
57205292872;57202775842;57222538092;56609777400;6506884322; |
Development of multithread acquisition system for high quality EEG signal measurement |
2021 |
Journal of Physics: Conference Series |
1816 |
1 |
012072 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103129496&doi=10.1088%2f1742-6596%2f1816%2f1%2f012072&partnerID=40&md5=8df825ddfea9b100797241af3b95358e |
Department of Physics, FMIPA Universitas Indonesia, Depok, 16424, Indonesia; Department of Physiology, Medical Faculty, Universitas Indonesia, Jakarta, 10430, Indonesia |
Apriadi, W., Department of Physics, FMIPA Universitas Indonesia, Depok, 16424, Indonesia; Gani, H.S., Department of Physics, FMIPA Universitas Indonesia, Depok, 16424, Indonesia; Prayitno, P., Department of Physics, FMIPA Universitas Indonesia, Depok, 16424, Indonesia; Ibrahim, N., Department of Physiology, Medical Faculty, Universitas Indonesia, Jakarta, 10430, Indonesia; Wijaya, S.K., Department of Physics, FMIPA Universitas Indonesia, Depok, 16424, Indonesia |
This work was concerned on development of the EEG acquisition and EEG signal processing by adding active electrodes and implementing multithread techniques. By using active electrodes, mounting them on the scalp surface would be easier to capture low signals of less than 1µV. The active electrodes were used to reduce noise when transfer signals from the electrode to the acquisition systems which equipped 20 gain. The verification was performed by comparing the active and passive electrodes using NETECH MiniSIM EEG Simulator 330. The advantage of this research was to reduce time delay for EEG signal computation on 32 channels. The acquisition system was based on Raspberry Pi and ADS1299 with multithread signal treatment. Signal filtering was performed into different threads and put all the EEG features into the database. A PC was used to process signal calculation such as processing FFT, signal feature extractions, and signal analysis. These calculations were divided into several functionally independent computations. The signals of each channel were calculated into different threads. The results of this work showed the effectiveness of the multithreaded method for processing large amounts of data (32 channels of 24 bits EEG signal) with low noise levels on the active electrodes. © Published under licence by IOP Publishing Ltd. |
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Electrodes; Acquisition systems; Active electrodes; Eeg acquisitions; EEG signal processing; Large amounts of data; Multithread techniques; Signal treatments; Transfer signals; Biomedical signal processing |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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605 |
Unggul D.B., Abdullah S., Rachman A. |
57221961543;57204563168;57217184320; |
Laterality condition analysis on non-arteritic anterior ischemic optic neuropathy patient in one of the hospital in Jakarta with medical data mining |
2021 |
Journal of Physics: Conference Series |
1725 |
1 |
012096 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100803241&doi=10.1088%2f1742-6596%2f1725%2f1%2f012096&partnerID=40&md5=38c1992b179967890ac62988e4c116ad |
Department of Mathematics, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, 10430, Indonesia |
Unggul, D.B., Department of Mathematics, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Abdullah, S., Department of Mathematics, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Rachman, A., Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, 10430, Indonesia |
Non-arteritic Anterior Ischemic Optic Neuropathy (NAION) is a disease caused by blood shortages in the artery that supplies the optic disc. Risk factors for NAION are hypertension, obesity, diabetes, dislipidemia, smoking, hypercoagulable state, cardiovascular disease, and stroke. NAION can result from unilateral or bilateral conditions. This study will focus on the identification of important factors that could distinguish characteristics between unilateral and bilateral patients. Random forest method is applied to obtain factors that can consistently distinguish characteristic between each laterality condition. Decision trees and the logistic regression method are added to obtain the visualization of the role of each important factors in the form of classification tree and the risk comparison of patients for experiencing a certain laterality condition by using odds ratios. The important factors based on random forest model are onset, fasting blood glucose levels, high density lipoprotein levels, age, two-hour postprandial glucose levels, and low density lipoprotein levels. Based on the odds ratio, advancing age and high density lipoprotein levels will decrease the risk of patients experiencing bilateral condition; on the other hand, the risk of bilateral condition will increase if other important factors are also increased. © 2021 Journal of Physics: Conference Series. |
Decision tree; Laterality; Logistic regression; Random forest |
Blood; Decision trees; Glucose; Lipoproteins; Logistic regression; Medical computing; Random forests; Blood glucose level; Cardio-vascular disease; Classification trees; High density lipoprotein levels; Logistic regression method; Low density lipoproteins; Random forest methods; Random forest modeling; Data mining |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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606 |
Hanifah N., Wiweko B., Bowolaksono A. |
57200075370;43061741400;57205093224; |
FSHR and LHR mRNA expression in granulosa cells of poor responder |
2021 |
Journal of Physics: Conference Series |
1725 |
1 |
012057 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100793552&doi=10.1088%2f1742-6596%2f1725%2f1%2f012057&partnerID=40&md5=498a20aef40d78ffcc6b9fa74da8dec6 |
Department of Biology, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Department of Obstetric and Gynecology, Faculty of Medicine, Universitas Indonesia, Depok, 16424, Indonesia |
Hanifah, N., Department of Biology, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Wiweko, B., Department of Obstetric and Gynecology, Faculty of Medicine, Universitas Indonesia, Depok, 16424, Indonesia; Bowolaksono, A., Department of Biology, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia |
In Vitro Fertilization (IVF) is one of the most commonly used procedures to help pregnancies in couples who have infertility problems. One of the problems of infertility is poor ovarian response and the woman who experiences it is known as poor responder. Poor responders do not have an adequate ovarian response to gonadotropin in ovarian stimulation. The success of fertilization in poor responders tends to be low due to low quantity and is generally followed by low oocyte quality. Gonadotropins consisting of FSH and LH, play a role in follicle development and ovulation. The follicle response in capturing gonadotropins depends on the exact bond between the hormone and its receptor (FSHR and LHR) in the granulosa cells surrounding the oocyte. The purpose of this research is to know the expression level of fshr and lhr mRNA in granulosa cells of poor responders through real-time PCR method which then tested statistically using t-test. Fourteen samples of each poor responders and normal women were used in this research. The results showed insignificant differences between expression level of fshr and lhr mRNA in granulosa cells of poor responders and normal women (p > 0.05). © 2021 Journal of Physics: Conference Series. |
FSHR; LHR; Poor ovarian response; Real-time PCR |
Cytology; Polymerase chain reaction; Expression levels; Follicle development; Granulosa cells; In-vitro; mRNA expression; Real-time PCR method; T-tests; Cells |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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607 |
Lestari D.A., Abdullah S., Rachman A. |
56119337300;57204563168;57217184320; |
Identification of factors associated with hypothyroidism due to radiotherapy in patients with nasopharyngeal cancer (Case study of nasopharyngeal cancer in one of the hospitals in Jakarta) |
2021 |
Journal of Physics: Conference Series |
1725 |
1 |
012027 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100793360&doi=10.1088%2f1742-6596%2f1725%2f1%2f012027&partnerID=40&md5=eb87ed0fd4bc75637854a08478652d08 |
Department of Mathematics, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, 10430, Indonesia |
Lestari, D.A., Department of Mathematics, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Abdullah, S., Department of Mathematics, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok, 16424, Indonesia; Rachman, A., Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, 10430, Indonesia |
Nasopharyngeal cancer is an abnormal cell growth that develops around the nasopharynx. Treatment of nasopharyngeal cancer patients includes chemotherapy or radiotherapy. Both treatments have side effects in patients. In this study, we will focus on hypothyroidism as a side effect of radiotherapy in the treatment of patients with nasopharyngeal cancer. Hypothyroidism is a condition when the thyroid gland is unable to produce enough thyroid hormone. The main goal of this study is to identify the factors associated with hypothyroidism. To achieve this goal, classification tree and logistic regression methods will be used. Classification tree is used to obtain important variables in the classification of subject classes. Then, logistic regression is used to quantify the risk of variables that appear in the classification tree, hypothyroidism risk factors, and hypothyroidism marker factors. Based on the analysis, it was found that the factors associated in this study were variable symptom, physical sign, smoking habits, gender, age, BMI (Body Mass Index), TSH (Thyroid Stimulating Hormone) and fT4 (free thyroxine) hormones, and also all items on Zulewski score, except items delayed ankle reflex and slow movements. These factors associated tended to increase the risk of hypothyroidism, except for the fT4 hormone and BMI. © 2021 Journal of Physics: Conference Series. |
Classification tree; Hypothyroidism; Logistic regression; Marker factors; Risk factors |
Cell proliferation; Chemotherapy; Hormones; Logistic regression; Radiotherapy; Body mass index; Classification trees; Logistic regression method; Nasopharyngeal cancer; Risk factors; Thyroid glands; Thyroid hormones; Thyroid stimulating hormones; Diseases |
IOP Publishing Ltd |
17426588 |
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Conference Paper |
Q4 |
210 |
18731 |
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