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Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory.

International journal of telemedicine and applications

Shaban-Nejad A, Ormandjieva O, Kassab M, Haarslev V.
PMID: 19343191
Int J Telemed Appl. 2009;2009:917826. doi: 10.1155/2009/917826. Epub 2009 Mar 30.

Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities...

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Shaban-Nejad A, Ormandjieva O, Kassab M, et al. Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory. Int J Telemed Appl. 2009;2009:917826doi: 10.1155/2009/917826.
Shaban-Nejad, A., Ormandjieva, O., Kassab, M., & Haarslev, V. (2009). Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory. International journal of telemedicine and applications, 2009917826. https://doi.org/10.1155/2009/917826
Shaban-Nejad, Arash, et al. "Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory." International journal of telemedicine and applications vol. 2009 (2009): 917826. doi: https://doi.org/10.1155/2009/917826
Shaban-Nejad A, Ormandjieva O, Kassab M, Haarslev V. Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory. Int J Telemed Appl. 2009;2009:917826. doi: 10.1155/2009/917826. Epub 2009 Mar 30. PMID: 19343191; PMCID: PMC2662492.
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The importance of competitiveness in new internationalized and competitive environment of pharmaceutical industry.

Iranian journal of pharmaceutical research : IJPR

Mehralian G, Shabaninejad H.
PMID: 25237330
Iran J Pharm Res. 2014;13(2):351-2.

No abstract available.

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Mehralian G, Shabaninejad H. The importance of competitiveness in new internationalized and competitive environment of pharmaceutical industry. Iran J Pharm Res. 2014;13(2):351-2
Mehralian, G., & Shabaninejad, H. (2014). The importance of competitiveness in new internationalized and competitive environment of pharmaceutical industry. Iranian journal of pharmaceutical research : IJPR, 13(2), 351-2.
Mehralian, Gholamhossein, and Shabaninejad, Hosein. "The importance of competitiveness in new internationalized and competitive environment of pharmaceutical industry." Iranian journal of pharmaceutical research : IJPR vol. 13,2 (2014): 351-2.
Mehralian G, Shabaninejad H. The importance of competitiveness in new internationalized and competitive environment of pharmaceutical industry. Iran J Pharm Res. 2014;13(2):351-2. PMID: 25237330; PMCID: PMC4157010.
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Colorimetric Sensor Based on .

International journal of analytical chemistry

Ghanizadeh Gerayeli F, Hosseini F, Bagheri Z, Savardashtaki A, Shabaninejad Z, Amani AM, Najafipour S.
PMID: 32612657
Int J Anal Chem. 2020 Jun 17;2020:5054864. doi: 10.1155/2020/5054864. eCollection 2020.

Zidovudine (ZDV) is an antiviral drug against HIV that was approved by the FDA on March, 1987. It is a reverse transcriptase inhibitor. This type of drug stops the reproduction of DNA and decreases the amount of the virus...

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Ghanizadeh Gerayeli F, Hosseini F, Bagheri Z, et al. Colorimetric Sensor Based on . Int J Anal Chem. 2020;2020:5054864doi: 10.1155/2020/5054864.
Ghanizadeh Gerayeli, F., Hosseini, F., Bagheri, Z., Savardashtaki, A., Shabaninejad, Z., Amani, A. M., & Najafipour, S. (2020). Colorimetric Sensor Based on . International journal of analytical chemistry, 20205054864. https://doi.org/10.1155/2020/5054864
Ghanizadeh Gerayeli, Farhad, et al. "Colorimetric Sensor Based on ." International journal of analytical chemistry vol. 2020 (2020): 5054864. doi: https://doi.org/10.1155/2020/5054864
Ghanizadeh Gerayeli F, Hosseini F, Bagheri Z, Savardashtaki A, Shabaninejad Z, Amani AM, Najafipour S. Colorimetric Sensor Based on . Int J Anal Chem. 2020 Jun 17;2020:5054864. doi: 10.1155/2020/5054864. eCollection 2020. PMID: 32612657; PMCID: PMC7317308.
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Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques.

JMIR mental health

Brenas JH, Shin EK, Shaban-Nejad A.
PMID: 31115344
JMIR Ment Health. 2019 May 21;6(5):e13498. doi: 10.2196/13498.

BACKGROUND: Adverse Childhood Experiences (ACEs), a set of negative events and processes that a person might encounter during childhood and adolescence, have been proven to be linked to increased risks of a multitude of negative health outcomes and conditions...

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Brenas JH, Shin EK, Shaban-Nejad A. Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques. JMIR Ment Health. 2019;6(5):e13498doi: 10.2196/13498.
Brenas, J. H., Shin, E. K., & Shaban-Nejad, A. (2019). Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques. JMIR mental health, 6(5), e13498. https://doi.org/10.2196/13498
Brenas, Jon Hael, et al. "Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques." JMIR mental health vol. 6,5 (2019): e13498. doi: https://doi.org/10.2196/13498
Brenas JH, Shin EK, Shaban-Nejad A. Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques. JMIR Ment Health. 2019 May 21;6(5):e13498. doi: 10.2196/13498. PMID: 31115344; PMCID: PMC6707574.
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A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability.

JMIR public health and surveillance

Al Manir MS, Brenas JH, Baker CJ, Shaban-Nejad A.
PMID: 29907554
JMIR Public Health Surveill. 2018 Jun 15;4(2):e10218. doi: 10.2196/10218.

BACKGROUND: According to the World Health Organization, malaria surveillance is weakest in countries and regions with the highest malaria burden. A core obstacle is that the data required to perform malaria surveillance are fragmented in multiple data silos distributed...

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Al Manir MS, Brenas JH, Baker CJ, et al. A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability. JMIR Public Health Surveill. 2018;4(2):e10218doi: 10.2196/10218.
Al Manir, M. S., Brenas, J. H., Baker, C. J., & Shaban-Nejad, A. (2018). A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability. JMIR public health and surveillance, 4(2), e10218. https://doi.org/10.2196/10218
Al Manir, Mohammad Sadnan, et al. "A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability." JMIR public health and surveillance vol. 4,2 (2018): e10218. doi: https://doi.org/10.2196/10218
Al Manir MS, Brenas JH, Baker CJ, Shaban-Nejad A. A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability. JMIR Public Health Surveill. 2018 Jun 15;4(2):e10218. doi: 10.2196/10218. PMID: 29907554; PMCID: PMC6026300.
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Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation.

JMIR medical informatics

Alghatani K, Ammar N, Rezgui A, Shaban-Nejad A.
PMID: 33949961
JMIR Med Inform. 2021 May 05;9(5):e21347. doi: 10.2196/21347.

BACKGROUND: Patient monitoring is vital in all stages of care. In particular, intensive care unit (ICU) patient monitoring has the potential to reduce complications and morbidity, and to increase the quality of care by enabling hospitals to deliver higher-quality,...

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Alghatani K, Ammar N, Rezgui A, et al. Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation. JMIR Med Inform. 2021;9(5):e21347doi: 10.2196/21347.
Alghatani, K., Ammar, N., Rezgui, A., & Shaban-Nejad, A. (2021). Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation. JMIR medical informatics, 9(5), e21347. https://doi.org/10.2196/21347
Alghatani, Khalid, et al. "Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation." JMIR medical informatics vol. 9,5 (2021): e21347. doi: https://doi.org/10.2196/21347
Alghatani K, Ammar N, Rezgui A, Shaban-Nejad A. Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation. JMIR Med Inform. 2021 May 05;9(5):e21347. doi: 10.2196/21347. PMID: 33949961; PMCID: PMC8135024.
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Proving the Correctness of Knowledge Graph Update: A Scenario From Surveillance of Adverse Childhood Experiences.

Frontiers in big data

Brenas JH, Shaban-Nejad A.
PMID: 34013202
Front Big Data. 2021 May 03;4:660101. doi: 10.3389/fdata.2021.660101. eCollection 2021.

Knowledge graphs are a modern way to store information. However, the knowledge they contain is not static. Instances of various classes may be added or deleted and the semantic relationship between elements might evolve as well. When such changes...

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Brenas JH, Shaban-Nejad A. Proving the Correctness of Knowledge Graph Update: A Scenario From Surveillance of Adverse Childhood Experiences. Front Big Data. 2021;4:660101doi: 10.3389/fdata.2021.660101.
Brenas, J. H., & Shaban-Nejad, A. (2021). Proving the Correctness of Knowledge Graph Update: A Scenario From Surveillance of Adverse Childhood Experiences. Frontiers in big data, 4660101. https://doi.org/10.3389/fdata.2021.660101
Brenas, Jon Haël, and Shaban-Nejad, Arash. "Proving the Correctness of Knowledge Graph Update: A Scenario From Surveillance of Adverse Childhood Experiences." Frontiers in big data vol. 4 (2021): 660101. doi: https://doi.org/10.3389/fdata.2021.660101
Brenas JH, Shaban-Nejad A. Proving the Correctness of Knowledge Graph Update: A Scenario From Surveillance of Adverse Childhood Experiences. Front Big Data. 2021 May 03;4:660101. doi: 10.3389/fdata.2021.660101. eCollection 2021. PMID: 34013202; PMCID: PMC8126660.
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β-Galactosidase: From its source and applications to its recombinant form.

Biotechnology and applied biochemistry

Movahedpour A, Ahmadi N, Ghalamfarsa F, Ghesmati Z, Khalifeh M, Maleksabet A, Shabaninejad Z, Taheri-Anganeh M, Savardashtaki A.
PMID: 33656174
Biotechnol Appl Biochem. 2021 Mar 03; doi: 10.1002/bab.2137. Epub 2021 Mar 03.

Carbohydrate-active enzymes are a group of important enzymes playing a critical role in the degradation and synthesis of carbohydrates. Glycosidases can hydrolyze glycosides into oligosaccharides, polysaccharides, and glycoconjugates via a cost-effective approach. Lactase is an important member of β-glycosidases...

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Movahedpour A, Ahmadi N, Ghalamfarsa F, et al. β-Galactosidase: From its source and applications to its recombinant form. Biotechnol Appl Biochem. 2021;doi: 10.1002/bab.2137.
Movahedpour, A., Ahmadi, N., Ghalamfarsa, F., Ghesmati, Z., Khalifeh, M., Maleksabet, A., Shabaninejad, Z., Taheri-Anganeh, M., & Savardashtaki, A. (2021). β-Galactosidase: From its source and applications to its recombinant form. Biotechnology and applied biochemistry, . https://doi.org/10.1002/bab.2137
Movahedpour, Ahmad, et al. "β-Galactosidase: From its source and applications to its recombinant form." Biotechnology and applied biochemistry vol. (2021). doi: https://doi.org/10.1002/bab.2137
Movahedpour A, Ahmadi N, Ghalamfarsa F, Ghesmati Z, Khalifeh M, Maleksabet A, Shabaninejad Z, Taheri-Anganeh M, Savardashtaki A. β-Galactosidase: From its source and applications to its recombinant form. Biotechnol Appl Biochem. 2021 Mar 03; doi: 10.1002/bab.2137. Epub 2021 Mar 03. PMID: 33656174.
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A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions With Disparities in Pediatric Surgery.

Frontiers in pediatrics

Akbilgic O, Shin EK, Shaban-Nejad A.
PMID: 33777865
Front Pediatr. 2021 Mar 12;9:620848. doi: 10.3389/fped.2021.620848. eCollection 2021.

No abstract available.

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Akbilgic O, Shin EK, Shaban-Nejad A. A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions With Disparities in Pediatric Surgery. Front Pediatr. 2021;9:620848doi: 10.3389/fped.2021.620848.
Akbilgic, O., Shin, E. K., & Shaban-Nejad, A. (2021). A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions With Disparities in Pediatric Surgery. Frontiers in pediatrics, 9620848. https://doi.org/10.3389/fped.2021.620848
Akbilgic, Oguz, et al. "A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions With Disparities in Pediatric Surgery." Frontiers in pediatrics vol. 9 (2021): 620848. doi: https://doi.org/10.3389/fped.2021.620848
Akbilgic O, Shin EK, Shaban-Nejad A. A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions With Disparities in Pediatric Surgery. Front Pediatr. 2021 Mar 12;9:620848. doi: 10.3389/fped.2021.620848. eCollection 2021. PMID: 33777865; PMCID: PMC7994338.
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Zimmermann-Laband syndrome: Clinical and cytogenetic study in two related patients.

Journal of clinical and experimental dentistry

Shirian S, Shahabinejad H, Saeedzadeh A, Daneshbod K, Khosropanah H, Mortazavi M, Daneshbod Y.
PMID: 31275518
J Clin Exp Dent. 2019 May 01;11(5):e452-e456. doi: 10.4317/jced.55214. eCollection 2019 May.

BACKGROUND: Zimmermann-Laband Syndrome (ZLS) is an extremely rare autosomal dominant congenital disorder. It is a craniofacial malformation syndrome with predominant intraoral involvement consisting of gingival fibromatosis diffusion in early development. The molecular basis of ZLS is still unknown. Although...

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Shirian S, Shahabinejad H, Saeedzadeh A, et al. Zimmermann-Laband syndrome: Clinical and cytogenetic study in two related patients. J Clin Exp Dent. 2019;11(5):e452-e456doi: 10.4317/jced.55214.
Shirian, S., Shahabinejad, H., Saeedzadeh, A., Daneshbod, K., Khosropanah, H., Mortazavi, M., & Daneshbod, Y. (2019). Zimmermann-Laband syndrome: Clinical and cytogenetic study in two related patients. Journal of clinical and experimental dentistry, 11(5), e452-e456. https://doi.org/10.4317/jced.55214
Shirian, Sadegh, et al. "Zimmermann-Laband syndrome: Clinical and cytogenetic study in two related patients." Journal of clinical and experimental dentistry vol. 11,5 (2019): e452-e456. doi: https://doi.org/10.4317/jced.55214
Shirian S, Shahabinejad H, Saeedzadeh A, Daneshbod K, Khosropanah H, Mortazavi M, Daneshbod Y. Zimmermann-Laband syndrome: Clinical and cytogenetic study in two related patients. J Clin Exp Dent. 2019 May 01;11(5):e452-e456. doi: 10.4317/jced.55214. eCollection 2019 May. PMID: 31275518; PMCID: PMC6599695.
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Health intelligence: how artificial intelligence transforms population and personalized health.

NPJ digital medicine

Shaban-Nejad A, Michalowski M, Buckeridge DL.
PMID: 31304332
NPJ Digit Med. 2018 Oct 02;1:53. doi: 10.1038/s41746-018-0058-9. eCollection 2018.

Advances in computational and data sciences for data management, integration, mining, classification, filtering, visualization along with engineering innovations in medical devices have prompted demands for more comprehensive and coherent strategies to address the most fundamental questions in health care...

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Shaban-Nejad A, Michalowski M, Buckeridge DL. Health intelligence: how artificial intelligence transforms population and personalized health. NPJ Digit Med. 2018;1:53doi: 10.1038/s41746-018-0058-9.
Shaban-Nejad, A., Michalowski, M., & Buckeridge, D. L. (2018). Health intelligence: how artificial intelligence transforms population and personalized health. NPJ digital medicine, 153. https://doi.org/10.1038/s41746-018-0058-9
Shaban-Nejad, Arash, et al. "Health intelligence: how artificial intelligence transforms population and personalized health." NPJ digital medicine vol. 1 (2018): 53. doi: https://doi.org/10.1038/s41746-018-0058-9
Shaban-Nejad A, Michalowski M, Buckeridge DL. Health intelligence: how artificial intelligence transforms population and personalized health. NPJ Digit Med. 2018 Oct 02;1:53. doi: 10.1038/s41746-018-0058-9. eCollection 2018. PMID: 31304332; PMCID: PMC6550150.
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The impact of emotional intelligence on managers' performance: Evidence from hospitals located in Tehran.

Journal of education and health promotion

Gorgi HA, Ahmadi A, Shabaninejad H, Tahmasbi A, Baratimarnani A, Mehralian G.
PMID: 26430690
J Educ Health Promot. 2015 Aug 06;4:63. doi: 10.4103/2277-9531.162383. eCollection 2015.

CONTEXT: Most of the studies show that emotional intelligence (EI) is an important factor for effective leadership and team performance in organizations.AIMS: This research paper aims to provide an exploratory analysis of EI in the hospitals managers located in...

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Gorgi HA, Ahmadi A, Shabaninejad H, et al. The impact of emotional intelligence on managers' performance: Evidence from hospitals located in Tehran. J Educ Health Promot. 2015;4:63doi: 10.4103/2277-9531.162383.
Gorgi, H. A., Ahmadi, A., Shabaninejad, H., Tahmasbi, A., Baratimarnani, A., & Mehralian, G. (2015). The impact of emotional intelligence on managers' performance: Evidence from hospitals located in Tehran. Journal of education and health promotion, 463. https://doi.org/10.4103/2277-9531.162383
Gorgi, Hasan Abolghasem, et al. "The impact of emotional intelligence on managers' performance: Evidence from hospitals located in Tehran." Journal of education and health promotion vol. 4 (2015): 63. doi: https://doi.org/10.4103/2277-9531.162383
Gorgi HA, Ahmadi A, Shabaninejad H, Tahmasbi A, Baratimarnani A, Mehralian G. The impact of emotional intelligence on managers' performance: Evidence from hospitals located in Tehran. J Educ Health Promot. 2015 Aug 06;4:63. doi: 10.4103/2277-9531.162383. eCollection 2015. PMID: 26430690; PMCID: PMC4579760.
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Showing 1 to 12 of 50 entries