Supply chain risk identification: a real-time data-mining approach by Deiva Ganesh, A., Kalpana, P.

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Factors influencing proactiveness in supply chain risk identification: A fuzzy-set qualitative comparative analysis by A, Deiva Ganesh, P, Kalpana

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An unusual neurological syndrome in a haemodialysis patient by Jose, Nisha, Jayaprakash, V, Deiva, A, Jayakumar, M

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Acute kidney injury in a patient treated with tenofovir alafenamide fumarate for Hepatitis B virus infection by Deiva, A, Jayaprakash, V, Jose, Nisha, Chandan Kumar, K, Jayakumar, M

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E.U. paediatric MOG consortium consensus: Part 1 – Classification of clinical phenotypes of paediatric myelin oligodendrocyte glycoprotein antibody-associated disorders by Bruijstens, Arlette L., Lechner, Christian, Flet-Berliac, Lorraine, Deiva, Kumaran, Neuteboom, Rinze F., Hemingway, Cheryl, Wassmer, Evangeline, Mog consortium, E.U. paediatric, Bruijstens, Arlette L., Wendel, Eva-Maria, Lechner, Christian, Breu, Markus, Flet-Berliac, Lorraine, de Chalus, Aliénor, Capobianco, Marco, Laetitia, Giorgi, Hemingway, Cheryl, Wassmer, Evangeline, Lim, Ming, Wickström, Ronny, Armangue, Thaís, Deiva, Kumaran, Neuteboom, Rinze F.

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Future of artificial intelligence and its influence on supply chain risk management – A systematic review by Deiva Ganesh, A., Kalpana, P.

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Safety and efficacy of teriflunomide in paediatric multiple sclerosis (TERIKIDS): a multicentre, double-blind, phase 3, randomised, placebo-controlled trial by Chitnis, Tanuja, Banwell, Brenda, Kappos, Ludwig, Arnold, Douglas L, Gücüyener, Kivilcim, Deiva, Kumaran, Skripchenko, Natalia, Cui, Li-Ying, Saubadu, Stephane, Hu, Wenruo, Benamor, Myriam, Le-Halpere, Annaig, Truffinet, Philippe, Tardieu, Marc, Dubois, Benedicte, Verhelst, Helene, Bojinova-Tchamova, Veneta, Mah, Jean, Cui, Li-Ying, Fang, Fang, Hao, Yunpeng, Jiang, Li, Li, Ling, Mao, Ding'An, Qiu, Wei, Tan, Guojun, Wu, Ye, Zhang, Meini, Zhou, Hongyu, Zhou, Shuizhen, Gross-Paju, Katrin, Cheuret, Emmanuel, Deiva, Kumaran, Edan, Giles, Vukusic, Sandra, Chrousos, George, Zafeiriou, Dimitrios, Achiron, Anat, Vaknin-Dembinsky, Adi, Yamout, Bassem, Laurynaitiene, Jurate, Vaiciene-Magistris, Nerija, Bojkovski, Vladimir, Trajkova, Vesna, Chaouki, Sana, Kissani, Najib, Neuteboom, Rinze, Palavra, Filipe, Belova, Anna, Boyko, Alexey, Evdoshenko, Evgeny, Kairbekova, Ekaterina, Malkova, Nadezhda, Shumilina, Maria, Skripchenko, Natalya, Nikolic, Dimitrije, Meca-Lallana, Jose, Triki, Chahnez Charfi, Chokri, Mhiri, Gouider, Riadh, Anlar, Banu, Gücüyener, Kivilcim, Hiz, Ayse Semra, Idiman, Egemen, Turkoglu, Recai, Yapici, Zuhal, Yilmaz, Unsal, Tantsura, Lyudmyla, Voloshyna, Nataliia, Lim, Ming, Wassmer, Evangeline, Cascione, Mark, Chitnis, Tanuja, LaGanke, Christopher, Rathke, Kevin, Scagnelli, John

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E.U. paediatric MOG consortium consensus: Part 2 – Neuroimaging features of paediatric myelin oligodendrocyte glycoprotein antibody-associated disorders by Baumann, Matthias, Bartels, Frederik, Finke, Carsten, Adamsbaum, Catherine, Hacohen, Yael, Rostásy, Kevin, Mog consortium, E.U. paediatric, Bruijstens, Arlette L., Wendel, Eva-Maria, Lechner, Christian, Breu, Markus, Flet-Berliac, Lorraine, de Chalus, Aliénor, Capobianco, Marco, Laetitia, Giorgi, Hemingway, Cheryl, Wassmer, Evangeline, Lim, Ming, Wickström, Ronny, Armangue, Thaís, Deiva, Kumaran, Neuteboom, Rinze F.

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E.U. paediatric MOG consortium consensus: Part 4 – Outcome of paediatric myelin oligodendrocyte glycoprotein antibody-associated disorders by Bruijstens, Arlette L., Breu, Markus, Wendel, Eva-Maria, Wassmer, Evangeline, Lim, Ming, Neuteboom, Rinze F., Wickström, Ronny, Mog consortium, E.U. paediatric, Bruijstens, Arlette L., Wendel, Eva-Maria, Lechner, Christian, Breu, Markus, Flet-Berliac, Lorraine, de Chalus, Aliénor, Capobianco, Marco, Laetitia, Giorgi, Hemingway, Cheryl, Wassmer, Evangeline, Lim, Ming, Wickström, Ronny, Armangue, Thaís, Deiva, Kumaran, Neuteboom, Rinze F.

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Segmentation and classification using image processing and supervising learning framework for mitosis detection in breast cancer mammographic images by Krithika, P, Ramesh, Sukruti, Satya, Padigi Reddy, Deiva Preetha, C A S

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Consensus statement: evaluation of new and existing therapeutics for pediatric multiple sclerosis by Chitnis, T, Tenembaum, S, Banwell, B, Krupp, L, Pohl, D, Rostasy, K, Yeh, E A, Bykova, O, Wassmer, E, Tardieu, M, Kornberg, A, Ghezzi, A

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Subcutaneous Interferon Beta-1a in Pediatric Multiple Sclerosis: A Retrospective Study by Tenembaum, Silvia N., Banwell, Brenda, Pohl, Daniela, Krupp, Lauren B., Boyko, Alexey, Meinel, Michael, Lehr, Lorenz, Rocak, Sanda, Cantogno, Elisabetta Verdun di, Moraga, Margaretha Stam, Ghezzi, Angelo

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Whole-body MR imaging in suspected physical child abuse: comparison with skeletal survey and bone scintigraphy findings from the PEDIMA prospective multicentre study by Proisy, Maïa, Vivier, Pierre-Hugues, Morel, Baptiste, Bruneau, Bertrand, Sembely-Taveau, Catherine, Vacheresse, Solène, Devillers, Anne, Lecloirec, Joseph, Bodet-Milin, Caroline, Dubois, Marine, Hamonic, Stéphanie, Bajeux, Emma, Ganivet, Anne, Adamsbaum, Catherine, Treguier, Catherine

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Nonparametric dynamically weighted combination model to determine when to stop testing by Deiva Preetha, C. A. S., Ramasamy, Subburaj

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Subcutaneous interferon β-1a in pediatric patients with multiple sclerosis: Regional differences in clinical features, disease management, and treatment outcomes in an internationa... by Krupp, Lauren B, Pohl, Daniela, Ghezzi, Angelo, Boyko, Alexey, Tenembaum, Silvia, Chen, Liang, Aycardi, Ernesto, Banwell, Brenda

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Dynamically Weighted Combination Model for Describing Inconsistent Failure Data of Software Projects by Ramasamy, Subburaj, Deiva Preetha, C. A. S.

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An Unusual Neurological Syndrome in a Haemodialysis Patient by Jose, Nisha, Jayaprakash, V, Deiva, A, Jayakumar, M

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Acute kidney injury in a patient treated with tenofovir alafenamide fumarate for Hepatitis B virus infection by Deiva, A, Jayaprakash, V, Jose, Nisha, Chandan Kumar, K N, Jayakumar, M

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Pediatric onset multiple sclerosis by Deiva, K.

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A systematic review of deep learning methods for the classification and segmentation of prostate cancer on magnetic resonance images by Nayagam, R. Deiva, Selvathi, D.

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