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125 results on '"ANWAAR, Muhammad"'

1. Safety and efficacy of colchicine for the prevention of post-operative atrial fibrillation in patients undergoing cardiac surgery: a meta-analysis of randomized controlled trials

Author

Agarwal, Siddharth, Beard, Christopher W, Khosla, Jagjit, Clifton, Shari, Anwaar, Muhammad Faraz, Ghani, Asad, Farhat, Kassem, Pyrpyris, Nikolaos, Momani, Joud, Munir, Muhammad Bilal, DeSimone, Christopher V, Deshmukh, Abhishek, Stavrakis, Stavros, Jackman, Warren M, Po, Sunny, and Asad, Zain Ul Abideen

Subjects
Clinical Research, Cardiovascular, Heart Disease, Clinical Trials and Supportive Activities, Prevention, Patient Safety, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Humans, Colchicine, Atrial Fibrillation, Randomized Controlled Trials as Topic, Cardiac Surgical Procedures, Incidence, Atrial fibrillation, Meta-analysis, Outcomes, Clinical Sciences, Cardiovascular System & Hematology
Abstract

Background and aimsColchicine is an anti-inflammatory drug that may prevent post-operative atrial fibrillation (POAF). The effect of this drug has been inconsistently shown in previous clinical trials. We aimed to compare the efficacy and safety of colchicine vs. placebo to prevent POAF in patients undergoing cardiac surgery.Methods and resultsA systematic search of EMBASE, MEDLINE, SCOPUS, ClinicalTrials.gov, and the Cochrane Library for randomized controlled trials (RCTs) was conducted from inception till April 2023. The primary outcome was the incidence of POAF after any cardiac surgery. The secondary outcome was the rate of drug discontinuation due to adverse events and adverse gastrointestinal events. Risk ratios (RR) were reported using the Mantel Haenszel method. A total of eight RCTs comprising 1885 patients were included. There was a statistically significant lower risk of developing POAF with colchicine vs. placebo (RR: 0.70; 95% CI: 0.59-0.82; P < 0.01, I2 = 0%), and this effect persisted across different subgroups. There was a significantly higher risk of adverse gastrointestinal events (RR: 2.20; 95% CI: 1.38-3.51; P < 0.01, I2 = 55%) with no difference in the risk of drug discontinuation in patients receiving colchicine vs. placebo (RR: 1.33; 95% CI: 0.93-1.89; P = 0.11, I2 = 0%).ConclusionThis meta-analysis of eight RCTs shows that colchicine is effective at preventing POAF, with a significantly higher risk of adverse gastrointestinal events but no difference in the rate of drug discontinuation. Future studies are required to define the optimal duration and dose of colchicine for the prevention of POAF.

Published
2023

2. On Leveraging Variational Graph Embeddings for Open World Compositional Zero-Shot Learning

Author

Anwaar, Muhammad Umer, Pan, Zhihui, and Kleinsteuber, Martin

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Humans are able to identify and categorize novel compositions of known concepts. The task in Compositional Zero-Shot learning (CZSL) is to learn composition of primitive concepts, i.e. objects and states, in such a way that even their novel compositions can be zero-shot classified. In this work, we do not assume any prior knowledge on the feasibility of novel compositions i.e.open-world setting, where infeasible compositions dominate the search space. We propose a Compositional Variational Graph Autoencoder (CVGAE) approach for learning the variational embeddings of the primitive concepts (nodes) as well as feasibility of their compositions (via edges). Such modelling makes CVGAE scalable to real-world application scenarios. This is in contrast to SOTA method, CGE, which is computationally very expensive. e.g.for benchmark C-GQA dataset, CGE requires 3.94 x 10^5 nodes, whereas CVGAE requires only 1323 nodes. We learn a mapping of the graph and image embeddings onto a common embedding space. CVGAE adopts a deep metric learning approach and learns a similarity metric in this space via bi-directional contrastive loss between projected graph and image embeddings. We validate the effectiveness of our approach on three benchmark datasets.We also demonstrate via an image retrieval task that the representations learnt by CVGAE are better suited for compositional generalization., Comment: Submitted to a conference

Published
2022

3. Variational Embeddings for Community Detection and Node Representation

Author

Khan, Rayyan Ahmad, Anwaar, Muhammad Umer, Kaddah, Omran, and Kleinsteuber, Martin

Subjects
Computer Science - Machine Learning
Abstract

In this paper, we study how to simultaneously learn two highly correlated tasks of graph analysis, i.e., community detection and node representation learning. We propose an efficient generative model called VECoDeR for jointly learning Variational Embeddings for Community Detection and node Representation. VECoDeR assumes that every node can be a member of one or more communities. The node embeddings are learned in such a way that connected nodes are not only "closer" to each other but also share similar community assignments. A joint learning framework leverages community-aware node embeddings for better community detection. We demonstrate on several graph datasets that VECoDeR effectively out-performs many competitive baselines on all three tasks i.e. node classification, overlapping community detection and non-overlapping community detection. We also show that VECoDeR is computationally efficient and has quite robust performance with varying hyperparameters.

Published
2021

4. Metapath- and Entity-aware Graph Neural Network for Recommendation

Author

Anwaar, Muhammad Umer, Han, Zhiwei, Arumugaswamy, Shyam, Khan, Rayyan Ahmad, Weber, Thomas, Qiu, Tianming, Shen, Hao, Liu, Yuanting, and Kleinsteuber, Martin

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

In graph neural networks (GNNs), message passing iteratively aggregates nodes' information from their direct neighbors while neglecting the sequential nature of multi-hop node connections. Such sequential node connections e.g., metapaths, capture critical insights for downstream tasks. Concretely, in recommender systems (RSs), disregarding these insights leads to inadequate distillation of collaborative signals. In this paper, we employ collaborative subgraphs (CSGs) and metapaths to form metapath-aware subgraphs, which explicitly capture sequential semantics in graph structures. We propose meta\textbf{P}ath and \textbf{E}ntity-\textbf{A}ware \textbf{G}raph \textbf{N}eural \textbf{N}etwork (PEAGNN), which trains multilayer GNNs to perform metapath-aware information aggregation on such subgraphs. This aggregated information from different metapaths is then fused using attention mechanism. Finally, PEAGNN gives us the representations for node and subgraph, which can be used to train MLP for predicting score for target user-item pairs. To leverage the local structure of CSGs, we present entity-awareness that acts as a contrastive regularizer on node embedding. Moreover, PEAGNN can be combined with prominent layers such as GAT, GCN and GraphSage. Our empirical evaluation shows that our proposed technique outperforms competitive baselines on several datasets for recommendation tasks. Further analysis demonstrates that PEAGNN also learns meaningful metapath combinations from a given set of metapaths.

Published
2020

5. Compositional Learning of Image-Text Query for Image Retrieval

Author

Anwaar, Muhammad Umer, Labintcev, Egor, and Kleinsteuber, Martin

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Information Retrieval
Abstract

In this paper, we investigate the problem of retrieving images from a database based on a multi-modal (image-text) query. Specifically, the query text prompts some modification in the query image and the task is to retrieve images with the desired modifications. For instance, a user of an E-Commerce platform is interested in buying a dress, which should look similar to her friend's dress, but the dress should be of white color with a ribbon sash. In this case, we would like the algorithm to retrieve some dresses with desired modifications in the query dress. We propose an autoencoder based model, ComposeAE, to learn the composition of image and text query for retrieving images. We adopt a deep metric learning approach and learn a metric that pushes composition of source image and text query closer to the target images. We also propose a rotational symmetry constraint on the optimization problem. Our approach is able to outperform the state-of-the-art method TIRG \cite{TIRG} on three benchmark datasets, namely: MIT-States, Fashion200k and Fashion IQ. In order to ensure fair comparison, we introduce strong baselines by enhancing TIRG method. To ensure reproducibility of the results, we publish our code here: \url{https://github.com/ecom-research/ComposeAE}., Comment: Published at IEEE WACV 2021

Published
2020

6. Epitomic Variational Graph Autoencoder

Author

Khan, Rayyan Ahmad, Anwaar, Muhammad Umer, and Kleinsteuber, Martin

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Variational autoencoder (VAE) is a widely used generative model for learning latent representations. Burda et al. in their seminal paper showed that learning capacity of VAE is limited by over-pruning. It is a phenomenon where a significant number of latent variables fail to capture any information about the input data and the corresponding hidden units become inactive. This adversely affects learning diverse and interpretable latent representations. As variational graph autoencoder (VGAE) extends VAE for graph-structured data, it inherits the over-pruning problem. In this paper, we adopt a model based approach and propose epitomic VGAE (EVGAE),a generative variational framework for graph datasets which successfully mitigates the over-pruning problem and also boosts the generative ability of VGAE. We consider EVGAE to consist of multiple sparse VGAE models, called epitomes, that are groups of latent variables sharing the latent space. This approach aids in increasing active units as epitomes compete to learn better representation of the graph data. We verify our claims via experiments on three benchmark datasets. Our experiments show that EVGAE has a better generative ability than VGAE. Moreover, EVGAE outperforms VGAE on link prediction task in citation networks.

Published
2020

9. Mend The Learning Approach, Not the Data: Insights for Ranking E-Commerce Products

Author

Anwaar, Muhammad Umer, Rybalko, Dmytro, and Kleinsteuber, Martin

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Improved search quality enhances users' satisfaction, which directly impacts sales growth of an E-Commerce (E-Com) platform. Traditional Learning to Rank (LTR) algorithms require relevance judgments on products. In E-Com, getting such judgments poses an immense challenge. In the literature, it is proposed to employ user feedback (such as clicks, add-to-basket (AtB) clicks and orders) to generate relevance judgments. It is done in two steps: first, query-product pair data are aggregated from the logs and then order rate etc are calculated for each pair in the logs. In this paper, we advocate counterfactual risk minimization (CRM) approach which circumvents the need of relevance judgements, data aggregation and is better suited for learning from logged data, i.e. contextual bandit feedback. Due to unavailability of public E-Com LTR dataset, we provide \textit{Mercateo dataset} from our platform. It contains more than 10 million AtB click logs and 1 million order logs from a catalogue of about 3.5 million products associated with 3060 queries. To the best of our knowledge, this is the first work which examines effectiveness of CRM approach in learning ranking model from real-world logged data. Our empirical evaluation shows that our CRM approach learns effectively from logged data and beats a strong baseline ranker ($\lambda$-MART) by a huge margin. Our method outperforms full-information loss (e.g. cross-entropy) on various deep neural network models. These findings demonstrate that by adopting CRM approach, E-Com platforms can get better product search quality compared to full-information approach. The code and dataset can be accessed at: https://github.com/ecom-research/CRM-LTR., Comment: Accepted for ECML-PKDD 2020

Published
2019

11. coMpliAnce with evideNce-based cliniCal guidelines in the managemenT of acute biliaRy pancreAtitis): The MANCTRA-1 international audit

Author

Podda, Mauro, Gerardi, Chiara, Coccolini, Federico, di Saverio, Salomone, Pellino, Gianluca, Pata, Francesco, Ielpo, Benedetto, Virdis, Francesco, Damaskos, Dimitris, Gourgiotis, Stavros, Poillucci, Gaetano, Pacella, Daniela, Jayant, Kumar, Agresta, Ferdinando, Sartelli, Massimo, Leppaniemi, Ari, Riboni, Cristiana, Catena, Fausto, Kluger, Yoram, Pisanu, Adolfo, Giordano, Alessio, Ferrario, Luca, Calvo, Mikel Prieto, Wilson, Michael, Soggiu, Fiammetta, Hamdan, Alaa, Gomes, Carlos Augusto, Fraga, Gustavo, Ioannidis, Argyrios, De Simone, Belinda, Demetrashvili, Zaza, Sahani, Saaz, Bains, Lovenish, Khamees, Almu'atasim, Ababneh, Hazim, Aljaiuossi, Osama, Pimentel, Samuel, Mohamad, Ikhwan Sani, Yusoff, Ahmad Ramzi, Zarnescu, Narcis Octavian, Calu, Valentin, Litvin, Andrey, Lesko, Dusan, Elmehrath, Ahmed, Elshami, Mohamedraed, de Santibañes, Martin, Gundara, Justin, Alawadhi, Kamel, Lui, Rashid, Julianov, Alexander, Ralon, Sergio, Garzali, Ibrahim-Umar, Machain, Gustavo M., Quispe-Cruz, Darwin Artidoro, Orantia, Abigail Cheska C., Walędziak, Maciej, Correia de Sá, Tiago, Ali, Syed Muhammad, Kovacevic, Bojan, Noel, Colin, Abdalah, Haidar M., Kchaou, Ali, Isik, Arda, Ansaloni, Luca, Biffl, Walter, Guerrieri, Mario, Sartori, Alberto, Abradelo, Manuel, Nigri, Giuseppe, Di Lorenzo, Nicola, Mingoli, Andrea, Chiarugi, Massimo, Di Menno Stavron, Juliana, Mazza, Oscar, Valenzuela, José Ignacio, Pantoja Pachajoa, Diana Alejandra, Alvarez, Fernando Andrés, Liaño, Julian Ezequiel, Tefay, Joan, Alshaikh, Abdulrahman, Hasan, Layla, Augusto Gomes, Carlos, Gomes, Felipe Couto, Fraga, Gustavo P., Calderan, Thiago R.A., Hirano, Elcio S., Dardanov, Dragomir, Saroglu, Azize, Atanasov, Boyko, Belev, Nikolay, Kovachev, Nikola, Chan, Shannon Melissa, Lok, Hon-Ting, Salcedo, Diego, Robayo, Diana, Triviño, María Alejandra, Manak, Jan, de Araujo, Jorann, Sethi, Ananya, Awad, Ahmed, Elbadawy, Merihan, Farid, Ahmed, Hanafy, Asmaa, Nafea, Ahmed, Sherief-Ghozy, Salah – Abbas, Alzhraa, Abdelsalam, Wafaa, Emile, Sameh, Elfallal, Ahmed, Elfeki, Hossam, Elghadban, Hosam, Shoma, Ashraf, Shetiwy, Mohamed, Elbahnasawy, Mohamed, Mohamed, Salem, Hamed, Emad Fawzi, Khalil, Usama Ahmed, Chouillard, Elie, Gumbs, Andrew, Police, Andréa, Mabilia, Andrea, Khutsishvili, Kakhi, Tvaladze, Anano, Ioannidis, Orestis, Anestiadou, Elissavet, Loutzidou, Lydia, Konstantinidis, Konstantinis, Konstantinidou, Sofia, Manatakis, Dimitrios, Acheimastos, Vasileios, Tasis, Nikolaos, Michalopoulos, Nikolaos, Kokoropoulos, Panagiotis, Papadoliopoulou, Maria, Sotiropoulou, Maria, Kapiris, Stylianos, Metaxas, Panagiotis, Tsouknidas, Ioannis, Kefili, Despoina, Petrakis, George, Dakis, Konstantinos, Alexandridou, Eirini, Synekidou, Eirini, Dakis, Kostas, Papadopoulos, Aristeidis, Chouliaras, Christos, Mouzakis, Odysseas, Mulita, Francesk, Maroulis, Ioannis, Vailas, Michail, Triantafyllou, Tania, Theodorou, Dimitrios, Lostoridis, Eftychios, Nagorni, Eleni-Aikaterini, Tourountzi, Paraskevi, Baili, Efstratia, Charalabopoulos, Alexandros, Liakakos, Theodore, Schizas, Dimitrios, Kozadinos, Alexandros, Syllaios, Athanasios, Machairas, Nikolaos, Kykalos, Stylianos, Stamopoulos, Paraskevas, Delis, Spiros, Farazi-Chongouki, Christos, Kalaitzakis, Evangelos, Giannarakis, Miltiadis, Lasithiotakis, Konstantinos, Petra, Giorgia, Gupta, Amit, Medappil, Noushif, Muthukrishnan, Vijayanand, Kamar, Jubin, Lal, Pawan, Agarwal, Rajendra, Magnoli, Matteo, Aonzo, Paolo, Serventi, Alberto, Giuliani, Antonio, Di Lascio, Pierpaolo, Pinto, Margherita, Bergamini, Carlo, Bottari, Andrea, Fortuna, Laura, Martellucci, Jacopo, Cicako, Atea, Miglietta, Claudio, Morino, Mario, Delogu, Daniele, Picchetto, Andrea, Assenza, Marco, D'Ambrosio, Giancarlo, Argenio, Giulio, Armellino, Mariano Fortunato, Ioia, Giovanna, Occhionorelli, Savino, Andreotti, Dario, Domenico, Lacavalla, Luppi, Davide, Casadei, Massimiliano, Di Donato, Luca, Manoochehri, Farshad, Lucia Marchese, Tiziana Rita, Sergi, William, Manca, Roberto, Murgia, Raimondo, Piras, Enrico, Conti, Lorenzo, Gianazza, Simone, Rizzi, Andrea, Segalini, Edoardo, Monti, Marco, Iiritano, Elena, Mariani, Nicolò Maria, De Nicola, Enrico, Scifo, Giovanna, Pignata, Giusto, Andreuccetti, Jacopo, Fleres, Francesco, Clarizia, Guglielmo, Spolini, Alessandro, Biloslavo, Alan, Germani, Paola, Mastronardi, Manuela, Bogoni, Selene, Palmisano, Silvia, De Manzini, Nicolo’, Marino, Marco Vito, Martines, Gennaro, Trigiante, Giuseppe, Lagouvardou, Elpiniki, Anania, Gabriele, Bombardini, Cristina, Oppici, Dario, Pilia, Tiziana, Murzi, Valentina, Gessa, Emanuela, Bracale, Umberto, Di Nuzzo, Maria Michela, Peltrini, Roberto, Salvetti, Francesco, Viganò, Jacopo, Sganga, Gabriele, Bianchi, Valentina, Fransvea, Pietro, Fontana, Tommaso, Sarro, Giuliano, Dinuzzi, Vincenza Paola, Scaravilli, Luca, Papa, Mario Virgilio, Jovine, Elio, Ciabatti, Giulia, Mastrangelo, Laura, Rottoli, Matteo, Ricci, Claudio, Russo, Iris Shari, Aiolfi, Alberto, Bona, Davide, Lombardo, Francesca, Cianci, Pasquale, Bini, Roberto, Chiara, Osvaldo, Cioffi, Stefano, Cantafio, Stefano, Coretti, Guido, Licitra, Edelweiss, Savino, Grazia, Grimaldi, Sergio, Porfidia, Raffaele, Moggia, Elisabetta, Garino, Mauro, Marafante, Chiara, Pesce, Antonio, Fabbri, Nicolò, Feo, Carlo Vittorio, Marra, Ester, Troian, Marina, Drigo, Davide, Nagliati, Carlo, Andrea, Muratore, Danna, Riccardo, Murgese, Alessandra, Crespi, Michele, Guerci, Claudio, Frontali, Alice, Ferrari, Luca, Favi, Francesco, Picariello, Erika, Rampini, Alessia, D'Acapito, Fabrizio, Ercolani, Giorgio, Solaini, Leonardo, Palmieri, Francesco, Calì, Matteo, Ferrara, Francesco, Muttillo, Irnerio Angelo, Muttillo, Edoardo Maria, Picardi, Biagio, Galleano, Raffaele, Badran, Ali, Ghazouani, Omar, Cervellera, Maurizio, Campanella, Gaetano, Papa, Gennaro, Di Bella, Annamaria, Perrone, Gennaro, Petracca, Gabriele Luciano, Prioriello, Concetta, Giuffrida, Mario, Cozzani, Federico, Rossini, Matteo, Inama, Marco, Butturini, Giovanni, Moretto, Gianluigi, Morelli, Luca, Di Candio, Giulio, Guadagni, Simone, Cicuttin, Enrico, Cremonini, Camilla, Tartaglia, Dario, Genovese, Valerio, Cillara, Nicola, Cannavera, Alessandro, Deserra, Antonello, Picciariello, Arcangelo, Papagni, Vincenzo, Vincenti, Leonardo, Bagaglini, Giulia, Sica, Giuseppe, Lapolla, Pierfrancesco, Brachini, Gioia, Bono, Dario, Nicotera, Antonella, Zago, Marcello, Sammartano, Fabrizio, Benuzzi, Laura, Stella, Marco, Rossi, Stefano, Cerioli, Alessandra, Puccioni, Caterina, Olmi, Stefano, Rubicondo, Carolina, Uccelli, Matteo, Balla, Andrea, Guida, Anna, Lepiane, Pasquale, Sasia, Diego, Giraudo, Giorgio, Salomone, Sara, Belloni, Elena, Cossa, Alessandra, Lancellotti, Francesco, Caronna, Roberto, Chirletti, Piero, Saullo, Paolina, Troiano, Raffaele, Mucilli, Felice, Barone, Mirko, Ippoliti, Massimo, Grande, Michele, Sensi, Bruno, Siragusa, Leandro, Ortenzi, Monica, Santini, Andrea, Di Carlo, Isidoro, Veroux, Massimiliano, Gioco, Rossella, Veroux, Gastone, Currò, Giuseppe, Ammendola, Michele, Komaei, Iman, Navarra, Giuseppe, Tonini, Valeria, Sartarelli, Lodovico, Vaccari, Samuele, Ceresoli, Marco, Perrone, Stefano, Roccamatisi, Linda, Millo, Paolo, Contul, Riccardo Brachet, Ponte, Elisa, Zuin, Matteo, Portale, Giuseppe, Tonello, Alice Sabrina, Fratini, Geri, Bianchini, Matteo, Perotti, Bruno, Doria, Emanuele, Lunghi, Elia Giuseppe, Visconti, Diego, Al-Shami, Khayry, Awadi, Sajeda, Khalil Buwaitel, Mohammad Musallam, Naief Naffa', Mo'taz Fawzat, Samhouri, Ahmad, Sawalha, Hatem, Ramzi Yusoff, Ahmad, Che Ani, Mohd Firdaus, Ahmed Fathil, Ida Nadiah, Huei, Jih, Zakaria, Andee Dzulkarnaen, Ya'acob, Mohammad Zawawi, Beristain-Hernandez, Jose-Luis, Garcia-Meza, Alejandro, Sepulveda-Rdriguez, Rafael, Lozada Hernández, Edgard Efren, Acuña Pinzón, Camilo Levi, Condoy, Jefferson Nieves, Becerra García, Francisco C., Sadik, Mohammad, Jalpa, kadir, Bushra, Devi, Jalpa, Seerani, Nandlal, Zainab, Asghar, Mohammad Sohail, Afzal, Ameer, Akbar, Ali, Lohse, Helmut Segovia, Lohse, Herald Segovia, Artidoro Quispe-Cruz, Darwin, Leon Cabrera, Zamiara Solange, Yamamoto Seto, Gaby Susana, Chiuyari, José Ríos, Ordemar, Jorge, Rodríguez, Martha, Orantia-Carlos, Abigail Cheska C., Quitoy, Margie Antionette, Kwiatkowski, Andrzej, Mawlichanów, Maciej, Rocha, Mónica, Soares, Carlos, Muhammad Ali, Syed, Stoian, Alexandru Rares, Diana Draghici, Andreea, Draghici, Andreea Diana, Grigorean, Valentin Titus, Radulescu, Raluca Bievel, Costea, Radu Virgil, Zarnescu, Eugenia Claudia, Kurtenkov, Mikhail, Gendrikson, George, Alla-Angelina, Volovich, Arina, Tsurbanova, Kaldarov, Ayrat, Gachabayov, Mahir, Abdullaev, Abakar, Milentijevic, Milica, Karamarkovic, Milovan, Panyko, Arpád, Radonak, Jozef, Soltes, Marek, Álvarez Morán, Laura, García, Haydée Calvo, Vega, Pilar Suárez, Estevez, Sergio, Ausania, Fabio, Farguell, Jordi, González-Abós, Carolina, Sánchez-Cabús, Santiago, Martín, Belén, Molina, Víctor, Oms, Luis, Ilzarbe, Lucas, Feijóo, Eva Pont, Perra, Elena Sofia, Rojas-Bonet, Noel, Penalba-Palmí, Rafael, Pérez-Bru, Susana, Tur-Martínez, Jaume, Álvarez-Torrado, Andrea, Domingo-Gonzalez, Marta, Tejedor-Tejada, Javier, Di Martino, Marcello, García del Alamo, Yaiza, Mendoza-Moreno, Fernando, García-Moreno-Nisa, Francisca, Matías-García, Belén, Durán, Manuel, Calleja-Lozano, Rafael, Perez de Villar, José Manuel, Sánchez-Guillén, Luis, Caravaca, Iban, Triguero-Cánovas, Daniel, Maya Aparicio, Antonio Carlos, Meléndez, Blas Durán, Palacios, Andrea Masiá, Landaluce-olavarria, Aitor, De Francisco, Mario, Estraviz-Mateos, Begoña, Alconchel, Felipe, Nicolás-López, Tatiana, Ramírez, Pablo, Muñoz-Cruzado, Virginia Duran, Ciuró, Felipe Pareja, Perea del Pozo, Eduardo, Pizarro, Sergio Olivares, Cabrera, Vicente Herrera, Bayo, Jose Muros, Hamid, Hytham K.S., Roesel, Raffaello, Cristaudi, Alessandra, Abbas, Kinan, Ali, Iyad, Tlili, Ahmed, Bayhan, Hüseyin, Türkoğlu, Mehmet Akif, Uzunoglu, Mustafa Yener, Azamat, Ibrahim Fethi, Omarov, Nail, Uymaz, Derya Salim, Altintoprak, Fatih, Akin, Emrah, First, Necattin, Das, Koray, Ozer, Nazmi, Seker, Ahmet, Kara, Yasin, Bozkurt, Mehmet Abdussamet, Kocataş, Ali, Atici, Semra Demirli, Akalin, Murat, Calik, Bulent, Colak, Elif, Altinel, Yuksel, Meric, Serhat, Aktimur, Yunus Emre, Hudson, Victoria, Duval, Jean-Luc, Khan, Mansoor, Saad, Ahmed, Kaur, Mandeep, Bradley, Alison, Fox, Katherine, Tomasi, Ivan, Beasley, Daniel, Prasanti, Alekhya Kotta, Kotecha, Pinky, Ebied, Husam, Paul, Michaela, Sheth, Hemant, Gerogiannis, Ioannis, Gaber, Mohannad, Sheikh, Zara, Seth, Shatadru, Kunitsyna, Maria, Leo, Cosimo Alex, Bellato, Vittoria, Zafar, Noman, Elserafy, Amr, Bond-smith, Giles, Tebala, Giovanni, Mathur, Pawan, Abid, Izza, Chidumije, Nnaemeka, Sandhar, Pardip, Zohaib Ullah, Syed Osama, Lezama, Tamara, Anwaar, Muhammad Hassan, Magee, Conor, Ahmed, Salma, Davies, Brooke, Apollos, Jeyakumar, McCormack, Kieran, Choudhary, Hasham, Doulias, Triantafyllos, Morrison, Tamsin, Palepa, Anna, Cal, Fernando Bonilla, Sánchez, Lianet, Domínguez, Fabiana, Al-Raimi, Ibrahim, Alshargabi, Haneen, Meead, Abdullah, Di Saverio, Salomone, Damaskos, Dimitrios, Agnoletti, Vanni, and Mole, Damian

Published
2022
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12. A Case Report of Kissing Carotid Arteries in the Retropharynx

Author

Siti Asmat Md Arepen, Azreen Zaira Abu Bakar, Nour Hanan Daniah Mohd Bakhit, Ahmad Anwaar Muhammad Saifullah, Nor Azirah Salahuddin, and Nor Eyzawiah Hassan

Subjects
arterial tortuosity, life-threatening, retropharyngeal, transoral surgeries, Otorhinolaryngology, RF1-547
Abstract

Introduction:An aberrant carotid artery has distinct terms and may exhibit a submucosal mass in the posterior pharyngeal wall. While it is primarily asymptomatic, an extreme aberrancy doubles the risk of dissection, a cerebrovascular accident (CVA) and an injury intraoperatively.Case Report:We report a case of ‘kissing carotid artery’ in a 65-year-old lady who presented with a foreign body sensation felt in the throat for one week. A finding of flexible nasopharyngolaryngoscopy (FNPLS) showed a bilateral paramedian retropharyngeal pulsating mass. Radiological examinations, including Computed Tomography (CT) of the neck and an angiogram, revealed an aberrant course of bilateral carotid arteries. In view of no malignancy and vascular malformations, there was no further intervention done, and the patient was subjected to yearly surveillance.Conclusion:Retropharyngeal carotid arteries are clinically significant anatomic variants. Such anomalies are potentially life-threatening and a risk factor for a severe hemorrhage during the simplest and commonly performed transoral surgeries. Thus, thorough perioperative assessment with accurate imaging techniques and studies are required to evaluate these anomalies and may avoid any disastrous complications.

Published
2022
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14. Unsupervised Learning of Joint Embeddings for Node Representation and Community Detection

Author

Khan, Rayyan Ahmad, Anwaar, Muhammad Umer, Kaddah, Omran, Han, Zhiwei, Kleinsteuber, Martin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Oliver, Nuria, editor, Pérez-Cruz, Fernando, editor, Kramer, Stefan, editor, Read, Jesse, editor, and Lozano, Jose A., editor

Published
2021
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15. Mend the Learning Approach, Not the Data: Insights for Ranking E-Commerce Products

Author

Anwaar, Muhammad Umer, Rybalko, Dmytro, Kleinsteuber, Martin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Yuxiao, editor, Ifrim, Georgiana, editor, Mladenić, Dunja, editor, Saunders, Craig, editor, and Van Hoecke, Sofie, editor

Published
2021
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20. Transcatheter Management of Tricuspid Regurgitation: A Review of Contemporary Evidence.

Author

Sammour, Yasser M., Anwaar, Muhammad Faraz, Cabral-Amador, Francisco, Garcia, Jian, Aoun, Joe, Kazmi, Sana, Faza, Nadeen, Little, Stephen H., Reardon, Michael J., Kleiman, Neal S., and Goel, Sachin S.

Subjects
*TRICUSPID valve surgery, *PATIENT selection, *PATIENT safety, *MEDICAL technology, *TREATMENT effectiveness, *TRICUSPID valve diseases, *CARDIAC catheterization, *CARDIAC surgery
Abstract

Tricuspid regurgitation (TR) is a common valvular heart disease that is associated with increased morbidity and mortality. Traditional surgical interventions, though definitive, carry considerable complexities and risks, especially for high-risk patients, with in-hospital mortality rates of ~9%. This resulted in the undertreatment of many patients with TR, creating a substantial unmet need. This has stimulated the development of transcatheter techniques, such as transcatheter tricuspid valve replacement, tricuspid edge-to-edge repair, tricuspid annuloplasty, caval valve implantation and many others, which offer less-invasive alternatives with promising early results and sustained benefits. This review provides a contemporary outlook on different transcatheter tricuspid valve interventions in patients with severe TR and assesses the existing clinical data regarding the safety and effectiveness of these devices in a rapidly expanding space. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Leveraging Representation Learning for Multi-Modal and Graph-Structured Data

Author

Kleinsteuber, Martin (Priv.-Doz. Dr.), Kleinsteuber, Martin (Priv.-Doz. Dr.);Steinbach, Eckehard (Prof. Dr.), Anwaar, Muhammad Umer, Kleinsteuber, Martin (Priv.-Doz. Dr.), Kleinsteuber, Martin (Priv.-Doz. Dr.);Steinbach, Eckehard (Prof. Dr.), and Anwaar, Muhammad Umer

Abstract

We devise novel representation learning methods for dealing with graph-structured and multi-modal data. We adopt a variational approach for jointly learning the node representation and community detection in graphs. We also adopt a variational graph based approach for the compositional zero-shot learning (CZSL) problem. An interesting application of CZSL is retrieving images from a database based on a multi-modal (image-text) query., Wir entwickeln neuartige Repräsentationslernmethoden für den Umgang mit graphenstrukturierten und multimodalen Daten.Wir verwenden einen variationalen Ansatz für das gemeinsame Lernen der Knotenrepräsentation und Gemeinschaftserkennung in Graphen. Wir verwenden auch variationalen, auf Graphen basierenden Ansatz für das Compositional Zero Shot Learning (CZSL) Problem. Eine interessante Anwendung von CZSL ist das Abrufen von Bildern aus Datenbank auf der Grundlage einer multimodalen Abfrage.

Published
2023

26. E-37 | Impact of Hypertrophic Cardiomyopathy on Mortality and Procedural Complications in Patients Undergoing Left Atrial Appendage Occlusion

Author

Agarwal, Siddharth, primary, Bansal, Agam, additional, Akhtar, Khawaja Hassan, additional, Khosla, Jagjit, additional, Anwaar, Muhammad Faraz, additional, Krishan, Satyam, additional, Khan, Jehanzeb, additional, Munir, Muhammad B., additional, Abideen Asad, Zain Ul, additional, and Baber, Usman, additional

Published
2023
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31. RACIAL DIFFERENCES IN THE OUTCOMES OF CATHETER ABLATION FOR ATRIAL FIBRILLATION IN PATIENTS WITH HEART FAILURE WITH PRESERVED EJECTION FRACTION: ANALYSIS FROM A NATIONAL REPRESENTATIVE DATABASE

Author

Agarwal, Siddharth, primary, Krishan, Satyam, additional, Khosla, Jagjit, additional, Bansal, Agam, additional, Khan, Jehanzeb, additional, Akhtar, Khawaja Hassan, additional, Anwaar, Muhammad Faraz, additional, Maheshwari, Supriya, additional, Khattab, Mahmood, additional, Faisaluddin, Mohammed, additional, Asad, Zain Ul Abideen, additional, and Stavrakis, Stavros, additional

Published
2023
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35. Der Einsatz von Methoden zum Repräsentationslernen von multimodalen und graph-strukturierten Daten

Author

Anwaar, Muhammad Umer, Kleinsteuber, Martin (Priv.-Doz. Dr.), and Steinbach, Eckehard (Prof. Dr.)

Subjects
Graphneuronale Netze, Repräsentationslernen, multimodale Daten, ddc:000, Informatik, Wissen, Systeme, Graph Neural Networks, Representation Learning, Multi modal Data
Abstract

We devise novel representation learning methods for dealing with graph-structured and multi-modal data. We adopt a variational approach for jointly learning the node representation and community detection in graphs. We also adopt a variational graph based approach for the compositional zero-shot learning (CZSL) problem. An interesting application of CZSL is retrieving images from a database based on a multi-modal (image-text) query. Wir entwickeln neuartige Repräsentationslernmethoden für den Umgang mit graphenstrukturierten und multimodalen Daten.Wir verwenden einen variationalen Ansatz für das gemeinsame Lernen der Knotenrepräsentation und Gemeinschaftserkennung in Graphen. Wir verwenden auch variationalen, auf Graphen basierenden Ansatz für das Compositional Zero Shot Learning (CZSL) Problem. Eine interessante Anwendung von CZSL ist das Abrufen von Bildern aus Datenbank auf der Grundlage einer multimodalen Abfrage.

Published
2023

39. Consequences and Adaptations in Medical Education during the COVID-19 Pandemic: Medical Students’ Perspective in a Malaysian Public Institution

Author

Suhaila Sanip, Mohd Rahman Omar, Maimunah Abdul Muna'aim, Nour Hanan Daniah Mohd Bakhit, and Ahmad Anwaar Muhammad Saifullah

Subjects
Medical education, Coronavirus disease 2019 (COVID-19), Political science, Perspective (graphical), Pandemic, Public institution
Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become one of the most disastrous health crises of the present world. The COVID-19 pandemic imposes unprecedented challenges for medical education globally. We describe how the pandemic has disrupted the medical education landscape from the students' perspectives and how medical students from a public higher institution adapted to the changes made to comply with the various government agencies' guidelines to contain the spread of COVID-19 while fulfilling the course requirements. The utilisation of numerous innovative online applications enabled the students to participate in numerous teaching and learning activities (TLA) with more flexible scheduling of the classes, participated in a series of online case-based discussions, clinical practice guideline (CPG) discussions, case presentations and objective structured clinical examination (OSCE) simulations. Students also joined TLAs conducted by other institutions both locally and abroad. In addition, students had collaborated among themselves and students from other institutions to conduct online peer-teaching activities. Perhaps, the main challenges for online classes were being unable to perform medical procedures and technical issues, commonly the poor internet connectivity. In regard to physical examinations, students performed it on members of their household instead of real patients. Learning medicine from a distance also gave us an opportunity to taste telemedicine which may be the future of medical practice. Students and academics should be adaptive, resourceful and resilient in facing these changes together. The institution needs to look at all stakeholders' perspectives to respond to the changes in the medical education landscape.

Published
2021
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40. Students’ Viewpoint: Challenges and Preparation of Medical Students for Final Clinical Examination during COVID-19

Author

Nour Hanan Daniah Mohd Bakhit, Ruhi Fadzlyana Jailani, and Ahmad Anwaar Muhammad Saifullah

Subjects
Medical education, Coronavirus disease 2019 (COVID-19), medicine.diagnostic_test, education, medicine, Physical examination, Psychology
Abstract

The COVID-19 pandemic has caused the clinical attachment for medical students to be deferred in ensuring reduction of viral transmission. Patients encounter was near impossible, thus suspending medical students’ clinical skills on real patients. Despite this, the final examination had to be conducted. Hence, appropriate planning was made to ensure candidates were well prepared. A paradigm shift was made by Universiti Sains Islam Malaysia (USIM) with regards to the medical education delivery and the final undergraduate examination organization. The traditional in-person teaching and learning sessions were converted to video conferences and small group discussions to ensure social distancing. Objective structured clinical examination (OSCE) consisting of sixteen manned and twenty unmanned stations were introduced to replace the conventional one long and three short cases clinical examinations. The pandemic became the biggest obstacle for the final year medical students physically and psychologically. Familiarisation with the new format of learning and examination has to be made within three months. Online learning materials became resourceful during revisions. Simulated OSCE conducted by the lecturers, were advantageous to the students in ensuring familiarity to the new examination technique. Role-plays involving students’ family members and colleagues as patients, aided the candidates to rehearse their physical examinations and history taking techniques. The intensive teaching and learning sessions have enabled the candidates to be equipped with the new examination requirement. Reflection: Generally, candidates favour OSCE over traditional clinical examinations. This preponderance was due to OSCE capability in assessing the entire aspects of knowledge and skills in variable rotations throughout medical school.

Published
2021
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41. Pneumocystis jirovecii Pneumonia Mimicking COVID-19 Pneumonia In A Patient With Newly Diagnosed Advanced HIV Disease

Author

Nour Hanan Daniah Mohd Bakhit, Sarah Zulaikha Samad, Mohd Rahman Omar, Ahmad Anwaar Muhammad Saifullah, Nor Safiqah Sharil, Assyifaa Nik Mazian, and Kim Yoon Siow

Subjects
medicine.medical_specialty, Pneumonia, Coronavirus disease 2019 (COVID-19), business.industry, Internal medicine, Pneumocystis jirovecii Pneumonia, medicine, Newly diagnosed, medicine.disease, business, Hiv disease
Abstract

During the pandemic, diagnosis of COVID-19 infection must be excluded in patients presenting with respiratory features, especially in the area where the incidence was high. This case report highlights a man who came with respiratory infection symptoms and the chest radiograph suspicious of COVID-19 pneumonia; however, his swab test for RT-PCR was negative for COVID-19. Later he was found to have a positive anti-HIV antibody and developed advanced HIV infection by multiple opportunistic infections. A 45-year-old man presented with chronic cough and dyspnea for three months which worsened five days before the presentation. It was associated with diarrhoea, dysphagia, weight loss, left lower limb weakness, with bowel and urinary incontinence. Chest auscultation revealed generalized crepitations. The first chest radiograph showed bilateral reticular opacities extending to the lung peripheries when the suspected diagnosis of COVID-19 pneumonia was made. The nasopharynx swab for RT-PCR for COVID-19 was negative, and the sputum was positive for Pneumocystis jirovecii. The contrast-enhanced CT (CECT) brain revealed changes consistent with brain abscess. The cerebrospinal fluid (CSF) examination was consistent with cryptococcal infection. He was initially treated in the Severe Acute Respiratory Infection (SARI) ward because of the initial impression of COVID-19. He was tested positive for Human Immunodeficiency Virus (HIV) rapid test and PCR, RPR and TPHA for syphilis. He was diagnosed with Pneumocystis jirovecii pneumonia, cryptococcal meningitis, brain abscess, oral and oesophageal candidiasis and syphilis. He was treated with co-trimoxazole, Amphotericin B, flucytosine, fluconazole, penicillin G and Nystatin. He initially improved upon treatment but later succumbed to his illnesses. Given the current situation of COVID-19, any patient with acute respiratory symptoms must be tested to rule out COVID-19 pneumonia. However, in a newly diagnosed advanced HIV patient presented with respiratory infection symptoms and extrapulmonary symptoms, opportunistic infections should be excluded along with COVID-19.

Published
2021
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