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1,435 results on '"Gomez *, Rafael"'

106. Umbilical incisional hernias (M3): are trocar-site hernias different? Comparative analysis of the EVEREG registry⋆

Author

Utrera González, Antonio, Capitán Vallvey, José M., Pradas, Matías, Pérez Gomar, Daniel, Bustos, Manuel, Herrera Fernández, Francisco Antonio, Blanco, Juan A., Robres Puig, Joaquim, Villalobos, Rafael, Güell Puigcercos, Dolors, Puigcercós Fusté, José María, Ayuso Osuna, Vicente, Piñol, Marta, Olona Casas, Carles, Martínez Ródenas, Francisco, Comajuncosas, Jordi, Sebastián Valverde, Enric, Amador, Sara, Gelonch, Jaume, Vallverdú, Helena, Abelló Sala, Magda, Veres Gómez, Antonio, Gamón, Rosa, García Peche, Pedro, González Valverde, Miguel, Martín Blanco, Miguel Ángel, Ferri, Ramón J, Martí Ciñat, Elena, García Pastor, Providencia, Montero, Carlos, Lorenzo Liñán, Miguel Ángel, Barbero, Vicente, Morlan, Miguel Ángel, Jover, José María, Delgado Lillo, Isabel, Sanz Sánchez, María Mercedes, Zarain Obrador, Leire, Lusilla, Alejandro, Cabeza Gómez, Juan Jesús, López, Antonio, Butrón, Teresa, Supelano Eslait, Guillermo, Álvarez Conde, José Luis, Pérez Saborido, Baltasar, Rodríguez López, Mario, Revuelta Álvarez, Santiago, Trillo Parejo, Pedro, Rodicio, José Luis, Blanco, Antonio, Cano Maldonado, Agustín Juan, Zorraquino González, Ángel, Guisasola, Esther, Fernández, Fernando, Granell, Javier, Bellido Luque, Juan Antonio, Rueda Pérez, Juan Manuel, Anaya Reig, Mª Pilar, Gómez Sabater, Rafael, García Díaz, Rosa Ana, Alonso, Verónica, Ciscar Belles, Ana, Makhoukhi, Touria, López-Cano, Manuel, Hernández Granados, Pilar, and Pereira Rodríguez, José Antonio

Published
2022
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108. Mortality Trends After Transfer From Peritoneal Dialysis to Hemodialysis

Author

Combes, Gill, Firanek, Catherine, Gomez, Rafael, Jha George, Vivek, Madero, Magdalena, Masakane, Ikuto, Misra, Madhukar, McDonald, Stephen, Mitra, Sandip, Moraes, Thyago, Mukhopadhyay, Puma, Sloand, James, Tong, Allison, Szeto, Cheuk-Chun, Nadeau-Fredette, Annie-Claire, Sukul, Nidhi, Lambie, Mark, Perl, Jeffrey, Davies, Simon, Johnson, David W., Robinson, Bruce, Van Biesen, Wim, Kramer, Anneke, Jager, Kitty J., Saran, Rajiv, Pisoni, Ronald, and Chan, Christopher T.

Published
2022
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115. Is It 'You' or 'Your Workplace'? Predictors of Job-Related Training in the Anglo-American World

Author

Barry, Michael, Gomez, Rafael, Kaufman, Bruce E., Wilkinson, Adrian, and Zhang, Tingting

Abstract

This paper examines the determinants of job-related training and workplace voice. Using data from a unique 2016 cross-national survey of Australian, British, Canadian and American employees, the paper contrasts two classic formulations in the literature; (1) the neoclassical/human capital approach which predicts that individual characteristics (such as age and education) which increase the efficiency of learning, will have the largest impact on the allocation of training (i.e. younger and more educated employees will be afforded training) and (2) the traditional institutional approach which favors the structural characteristics present at the industry and firm level, the nature of the job itself and the strategic choices of firms as the major predictors of job-related training. We find that age -- a key factor in the human capital model -- plays a significant role in the allocation of training but that education (in keeping with recent evidence) does not. In sum the human capital model provides, at best, only a partial explanation for the differences in training observed across individuals. In contrast, variables invoked by the institutional literature (i.e. occupation level; industry; ownership type; and market structure) are highly significant and account for a much greater proportion of the variance in training observed across workers. Other institutional factors such as the presence of a union and a human resource department were strong positive predictors of job-related training. But most important were product-market strategy and employee voice. Respondents working in firms utilizing a 'high road/high quality' product/service strategy and with a workplace consultative committee were significantly more likely to receive training than similar workers employed in observably similar firms. This last finding supports the industrial relations view of voice as an important channel by which training is optimally delivered inside the firm.

Published
2020
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116. Measuring Intangible Outcomes Can Be Problematic: The Challenge of Assessing Learning during International Short-Term Study Experiences

Author

Cushing, Debra Flanders, Pennings, Mark, Willox, Dino, Gomez, Rafael, Dyson, Clare, and Coombs, Courtney

Abstract

Short-term international study experiences, or study tours, aim to increase students' global awareness, educate and empower them to be productive global citizens, and contribute to their future employability. Learning outcomes from study tours often include intangible personal characteristics or soft skills, as opposed to specific disciplinary skills and knowledge, and yet, these are not easily identified. Using an iterative Delphi process, this study aimed to understand the pedagogical experience of tour leaders (experts) and assist in future development of effective assessment. Findings include four key areas of agreement among the experts: (1) both discipline-based knowledge and the acquisition of intangible personal characteristics are important learning outcomes and are considered to be almost equally important, (2) assessment almost always occurs on tour, (3) formative assessment for learning is predominantly used (rather than learning for summative assessment to test the learning), and (4) facilitated reflection is an important way to encourage learning during a study tour. Yet, the findings also reveal uncertainty about assessing outcomes that include intangible personal characteristics and soft skills. The article concludes with pedagogical implications and recommendations for future research.

Published
2019
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120. Closing the Execution Gap in Generative AI for Chemicals and Materials: Freeways or Safeguards

Author

Subramanian, Akshay, primary, Gao, Wenhao, additional, Barzilay, Regina, additional, Grossman, Jeffrey C., additional, Jaakkola, Tommi, additional, Jegelka, Stefanie, additional, Li, Mingda, additional, Li, Ju, additional, Matusik, Wojciech, additional, Olivetti, Elsa, additional, Coley, Connor W., additional, and Gomez-Bombarelli, Rafael, additional

Published
2024
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121. One-Pot Synthesis of CHA/ERI-Type Zeolite Intergrowth from a Single Multiselective Organic Structure-Directing Agent

Author

Kwon, Soonhyoung, primary, Bello-Jurado, Estefanía, additional, Ikonnikova, Evgeniia, additional, Lee, Hwajun, additional, Schwalbe-Koda, Daniel, additional, Corma, Avelino, additional, Willhammar, Tom, additional, Olivetti, Elsa A., additional, Gomez-Bombarelli, Rafael, additional, Moliner, Manuel, additional, and Román-Leshkov, Yuriy, additional

Published
2024
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123. Teacher RePlay and Children ReAct: pilot testing a formative toolkit to support playful learning in the classroom

Author

Omoeva, Carina, primary, Zosh, Jennifer M., additional, Pyle, Angela, additional, D'Sa, Nikhit, additional, Contreras Gomez, Rafael, additional, Dooley, Brian, additional, Giacomazzi, Mauro, additional, Ariapa, Martin, additional, Maldonado-Carreño, Carolina, additional, Escallón, Eduardo, additional, Dey, Gopal, additional, Pavel, Kazi Ferdous, additional, and Laverty, Ciara, additional

Published
2024
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125. Generative Models for Automatic Chemical Design

Author

Schwalbe-Koda, Daniel, Gómez-Bombarelli, Rafael, Beiglböck, Wolf, Founding Editor, Ehlers, Jürgen, Founding Editor, Hepp, Klaus, Founding Editor, Weidenmüller, Hans-Arwed, Founding Editor, Bartelmann, Matthias, Series Editor, Citro, Roberta, Series Editor, Hänggi, Peter, Series Editor, Hjorth-Jensen, Morten, Series Editor, Lewenstein, Maciej, Series Editor, Rubio, Angel, Series Editor, Salmhofer, Manfred, Series Editor, Schleich, Wolfgang, Series Editor, Theisen, Stefan, Series Editor, Wells, James D., Series Editor, Zank, Gary P., Series Editor, Schütt, Kristof T., editor, Chmiela, Stefan, editor, von Lilienfeld, O. Anatole, editor, Tkatchenko, Alexandre, editor, Tsuda, Koji, editor, and Müller, Klaus-Robert, editor

Published
2020
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129. Automatic chemical design using a data-driven continuous representation of molecules

Author

Gómez-Bombarelli, Rafael, Wei, Jennifer N., Duvenaud, David, Hernández-Lobato, José Miguel, Sánchez-Lengeling, Benjamín, Sheberla, Dennis, Aguilera-Iparraguirre, Jorge, Hirzel, Timothy D., Adams, Ryan P., and Aspuru-Guzik, Alán

Subjects
Computer Science - Learning, Physics - Chemical Physics
Abstract

We report a method to convert discrete representations of molecules to and from a multidimensional continuous representation. This model allows us to generate new molecules for efficient exploration and optimization through open-ended spaces of chemical compounds. A deep neural network was trained on hundreds of thousands of existing chemical structures to construct three coupled functions: an encoder, a decoder and a predictor. The encoder converts the discrete representation of a molecule into a real-valued continuous vector, and the decoder converts these continuous vectors back to discrete molecular representations. The predictor estimates chemical properties from the latent continuous vector representation of the molecule. Continuous representations allow us to automatically generate novel chemical structures by performing simple operations in the latent space, such as decoding random vectors, perturbing known chemical structures, or interpolating between molecules. Continuous representations also allow the use of powerful gradient-based optimization to efficiently guide the search for optimized functional compounds. We demonstrate our method in the domain of drug-like molecules and also in the set of molecules with fewer that nine heavy atoms., Comment: 26 pages, 8 figures

Published
2016
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130. Photocell Optimisation Using Dark State Protection

Author

Fruchtman, Amir, Gómez-Bombarelli, Rafael, Lovett, Brendon W., and Gauger, Erik M.

Subjects
Quantum Physics, Physics - Chemical Physics
Abstract

Conventional photocells suffer a fundamental efficiency threshold imposed by the principle of detailed balance, reflecting the fact that good absorbers must necessarily also be fast emitters. This limitation can be overcome by `parking' the energy of an absorbed photon in a dark state which neither absorbs nor emits light. Here we argue that suitable dark states occur naturally as a consequence of the dipole-dipole interaction between two proximal optical dipoles for a wide range of realistic molecular dimers. We develop an intuitive model of a photocell comprising two light-absorbing molecules coupled to an idealised reaction centre, showing asymmetric dimers are capable of providing a significant enhancement of light-to-current conversion under ambient conditions. We conclude by describing a roadmap for identifying suitable molecular dimers for demonstrating this effect by screening a very large set of possible candidate molecules., Comment: 14 pages, 16 figures, comments are very welcome!

Published
2015
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132. Controversies in optimal anemia management: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Conference

Author

Abu-Alfa, Ali K., Afsar, Baris, Pai, Amy Barton, Besarab, Anatole, Moore, Geraldine Biddle, Casadevall, Nicole, Cases, Aleix, de Francisco, Angel, Eckardt, Kai-Uwe, Fishbane, Steven, Fried, Linda F., Ganz, Tomas, Ginzburg, Yelena Z., Gómez, Rafael, Goodnough, Lawrence T., Hamano, Takayuki, Hanudel, Mark R., Hao, Chuan-Ming, Iseki, Kunitoshi, Ix, Joachim H., Johansen, Kirsten L., Ketteler, Markus, Kovesdy, Csaba P., Leaf, David E., Macdougall, Iain C., Massy, Ziad A., McMahon, Lawrence P., Minutolo, Roberto, Nakanishi, Takeshi, Nemeth, Elizabeta, Obrador, Gregorio T., Parfrey, Patrick S., Park, Hyeong-Cheon, Pecoits-Filho, Roberto, Robinson, Bruce M., Roger, Simon D., Shah, Yatrik M., Spinowitz, Bruce S., Tanaka, Tetsuhiro, Tsukamoto, Yusuke, Tungsanga, Kriang, Walther, Carl P., Yee-Moon Wang, Angela, Wolf, Myles, Babitt, Jodie L., Eisenga, Michele F., Haase, Volker H., Kshirsagar, Abhijit V., Levin, Adeera, Locatelli, Francesco, Małyszko, Jolanta, Swinkels, Dorine W., Tarng, Der-Cherng, Cheung, Michael, Jadoul, Michel, Winkelmayer, Wolfgang C., and Drüeke, Tilman B.

Published
2021
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136. Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Author

Xie, Tian, France-Lanord, Arthur, Wang, Yanming, Lopez, Jeffrey, Stolberg, Michael A., Hill, Megan, Leverick, Graham Michael, Gomez-Bombarelli, Rafael, Johnson, Jeremiah A., Shao-Horn, Yang, Grossman, Jeffrey C., Xie, Tian, France-Lanord, Arthur, Wang, Yanming, Lopez, Jeffrey, Stolberg, Michael A., Hill, Megan, Leverick, Graham Michael, Gomez-Bombarelli, Rafael, Johnson, Jeremiah A., Shao-Horn, Yang, and Grossman, Jeffrey C.

Abstract

Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.

Published
2024

137. Examining graph neural networks for crystal structures: Limitations and opportunities for capturing periodicity

Author

Gong, Sheng, Yan, Keqiang, Xie, Tian, Shao-Horn, Yang, Gomez-Bombarelli, Rafael, Ji, Shuiwang, Grossman, Jeffrey C., Gong, Sheng, Yan, Keqiang, Xie, Tian, Shao-Horn, Yang, Gomez-Bombarelli, Rafael, Ji, Shuiwang, and Grossman, Jeffrey C.

Abstract

Graph neural networks (GNNs) have recently been used to learn the representations of crystal structures through an end-to-end data-driven approach. However, a systematic top-down approach to evaluate and understand the limitations of GNNs in accurately capturing crystal structures has yet to be established. In this study, we introduce an approach using human-designed descriptors as a compendium of human knowledge to investigate the extent to which GNNs can comprehend crystal structures. Our findings reveal that current state-of-the-art GNNs fall short in accurately capturing the periodicity of crystal structures. We analyze this failure by exploring three aspects: local expressive power, long-range information processing, and readout function. To address these identified limitations, we propose a straightforward and general solution: the hybridization of descriptors with GNNs, which directly supplements the missing information to GNNs. The hybridization enhances the predictive accuracy of GNNs for specific material properties, most notably phonon internal energy and heat capacity, which heavily rely on the periodicity of materials.

Published
2024

138. Chemistry-Informed Machine Learning for Polymer Electrolyte Discovery

Author

Bradford, Gabriel, Lopez, Jeffrey, Ruza, Jurgis, Stolberg, Michael A., Osterude, Richard, Johnson, Jeremiah A., Gomez-Bombarelli, Rafael, Shao-Horn, Yang, Bradford, Gabriel, Lopez, Jeffrey, Ruza, Jurgis, Stolberg, Michael A., Osterude, Richard, Johnson, Jeremiah A., Gomez-Bombarelli, Rafael, and Shao-Horn, Yang

Abstract

Solid polymer electrolytes (SPEs) have the potential to improve lithium-ion batteries by enhancing safety and enabling higher energy densities. However, SPEs suffer from significantly lower ionic conductivity than liquid and solid ceramic electrolytes, limiting their adoption in functional batteries. To facilitate more rapid discovery of high ionic conductivity SPEs, we developed a chemistry-informed machine learning model that accurately predicts ionic conductivity of SPEs. The model was trained on SPE ionic conductivity data from hundreds of experimental publications. Our chemistry-informed model encodes the Arrhenius equation, which describes temperature activated processes, into the readout layer of a state-of-the-art message passing neural network and has significantly improved accuracy over models that do not encode temperature dependence. Chemically informed readout layers are compatible with deep learning for other property prediction tasks and are especially useful where limited training data are available. Using the trained model, ionic conductivity values were predicted for several thousand candidate SPE formulations, allowing us to identify promising candidate SPEs. We also generated predictions for several different anions in poly(ethylene oxide) and poly(trimethylene carbonate), demonstrating the utility of our model in identifying descriptors for SPE ionic conductivity.

Published
2024

139. Effectiveness and safety of XEN63 in patients with primary-open-angle glaucoma

Author

Martínez De La Casa Fernández-Borrella, José María, Marcos Parra, María Teresa, Millá Griñó, Elena, Laborda, Teresa, Giménez Gomez, Rafael, Larrosa, José Manuel, Urcola, Aritz, Teus, Miguel Ángel, Perucho Martínez, Susana, Martínez De La Casa Fernández-Borrella, José María, Marcos Parra, María Teresa, Millá Griñó, Elena, Laborda, Teresa, Giménez Gomez, Rafael, Larrosa, José Manuel, Urcola, Aritz, Teus, Miguel Ángel, and Perucho Martínez, Susana

Abstract

This paper evaluates the effectiveness and safety of XEN63 stent, either standalone or in combination with phacoemulsification, in patients with primary open-angle glaucoma (POAG). Eighty eyes from 80 patients with medically uncontrolled POAG were assigned to undergo XEN63 implant. The primary outcome was the surgical success, defined as an intraocular pressure (IOP) lowering from preoperative values ≥ 20% and an IOP absolute value between 6 and 18 mmHg, with or without antiglaucoma medications. Forty-three (53.7%) eyes underwent XEN63-standalone and 37(46.2%) eyes a XEN63 + Phacoemulsification procedure. Success rate was 68.8% (55/80) eyes in the overall study sample, 69.8% (30/43) eyes in the XEN63-standalone group; and 67.6% (25/37) eyes in the XEN63 + Phaco group (p = 0.6133). Preoperative IOP was significantly lowered from 22.1 ± 4.9 mmHg and 19.8 ± 3.7 mmHg to 14.7 ± 5.3 mmHg and 13.8 ± 3.4 mmHg in the XEN63-standalone and XEN63 + Phaco groups, respectively (p < 0.0001 each, respectively); without significant differences between them at any of the time-points measured. Preoperative number of ocular-hypotensive drugs was significantly reduced from 2.3 ± 0.8 to 0.3 ± 0.7 drugs, from 2.5 ± 0.7 to 0.3 ± 0.7 drugs; and from 2.0 ± 0.8 to 0.3 ± 0.7 drugs, in the overall, XEN63-standalone, and XEN63 + Phaco groups, respectively. Regarding safety, 3(42.5%) eyes had transient hypotony at some point during the study, although only in one (1.2%) eye was clinically significant. Four (5.0%) eyes underwent a needling, 4 (5.0%) eyes underwent surgical-bleb-revision, 1 (1.2%) eye required a device replacement and 1 (1.2%) eye a device removal due to maculopathy. XEN63, either alone or in combination with phacoemulsification, significantly lowered IOP and reduced the number of ocular hypotensive medications. The rate of ocular hypotony was relatively high, although it was clinically relevant only in one eye., Depto. de Inmunología, Oftalmología y ORL, Unidad Docente de Inmunología, Oftalmología y ORL, Fac. de Óptica y Optometría, TRUE, pub

Published
2024

141. Convolutional Networks on Graphs for Learning Molecular Fingerprints

Author

Duvenaud, David, Maclaurin, Dougal, Aguilera-Iparraguirre, Jorge, Gómez-Bombarelli, Rafael, Hirzel, Timothy, Aspuru-Guzik, Alán, and Adams, Ryan P.

Subjects
Computer Science - Learning, Computer Science - Neural and Evolutionary Computing, Statistics - Machine Learning
Abstract

We introduce a convolutional neural network that operates directly on graphs. These networks allow end-to-end learning of prediction pipelines whose inputs are graphs of arbitrary size and shape. The architecture we present generalizes standard molecular feature extraction methods based on circular fingerprints. We show that these data-driven features are more interpretable, and have better predictive performance on a variety of tasks., Comment: 9 pages, 5 figures. To appear in Neural Information Processing Systems (NIPS)

Published
2015

142. Gaining 'Raw Insider Knowledge': The Benefits and Challenges of International Study Tours for Creative Industries Students

Author

Pennings, Mark, Cushing, Debra Flanders, Gomez, Rafael, Dyson, Clare, and Coombs, Courtney

Abstract

International short-term study tours are a fast-growing format for outbound education and provide exciting experiential learning opportunities for students in the creative industries disciplines. This success has encouraged researchers to seek a comprehensive view of the various concrete experiences that contribute to student learning during study tours. To that end, this article presents evidence from a qualitative online post-tour questionnaire administered with students studying various art and design disciplines who participated in short-term international study tours at a large Australian university in 2015. Using Kolb's Experiential Learning Theory as a framework, data collected explored student perceptions of which concrete experiences on a study tour are most impactful and which may actually hinder learning. Findings revealed: experiencing key industry venues are the most significant aspects of a study tour, rather than networking or personal growth; poor itinerary planning and travel issues are the least liked aspects of a tour, yet are often the most easily addressed with better tour management and planning; and students were positively impacted by unexpected gains in knowledge about their creative industries discipline. This study, therefore, provides unique insights into which concrete experiences may be most impactful as part of the experiential learning cycle within an international study tour for creative industries students.

Published
2019
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144. Monitoring of COVID-19 patients via telemedicine with telemonitoring

Author

Martínez-García, M., Bal-Alvarado, M., Santos Guerra, F., Ares-Rico, R., Suárez-Gil, R., Rodríguez-Álvarez, A., Pérez-López, A., Casariego-Vales, E., Fernández Rial, Álvaro, Rabuñal Rey, Ramón, Rodríguez Álvarez, Ana, Pérez López, Antía, Golpe Gómez, Rafael, Gil Mouce, Cristina, Suárez Ramírez, Nicolás, Almuiña Simón, Carmen, José Cereijo Quinteiro, María, Daporta Rodríguez, Luis, Fernández Valdivieso, Elvira, Vázquez Fernández, Andrés, Barcia Losada, Andrea, García Martínez, Arantza, Portero Vázquez, Amparo, Trillo Dono, Natalia, Revilla Villegas, Concepción, Fernández Rodríguez, Raquel, García Armesto, Isabel, Giadas Piñeiro, Rocío, Rosa Rodríguez Macía, Ana, Carballada González, Francisco, Núñez Orjales, Ramón, Martin Lázaro, Joaquín, Alfredo González Guzmán, Luis, Mar Abad García, María, Gloria Álvarez Silveiro, María, Carmen Coria Abel, María, Díaz Sánchez, Javier, Jesús Freire Regueiro, María, María Casanova Quiñoá, Ana, José Dobao Feijoo, María, Luisa Fernández Rodríguez, María, Rey Ponce, Ángela, Monte Secades, Rafael, Jesús Pérez Taboada, María, Sánchez Fernández, Rafael, Pérez Peña, Juan, Pereira, Manuel, and Conde Freire, Jesús

Published
2020
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145. Telemedicina con telemonitorización en el seguimiento de pacientes con COVID-19

Author

Fernández Rial, Álvaro, Rabuñal Rey, Ramón, Rodríguez Álvarez, Ana, Pérez López, Antía, Golpe Gómez, Rafael, Gil Mouce, Cristina, Suárez Ramírez, Nicolás, Almuiña Simón, Carmen, José Cereijo Quinteiro, María, Daporta Rodríguez, Luis, Fernández Valdivieso, Elvira, Vázquez Fernández, Andrés, Barcia Losada, Andrea, García Martínez, Arantza, Portero Vázquez, Amparo, Trillo Dono, Natalia, Revilla Villegas, Concepción, Fernández Rodríguez, Raquel, García Armesto, Isabel, Giadas Piñeiro, Rocío, Rosa Rodríguez Macía, Ana, Carballada González, Francisco, Núñez Orjales, Ramón, Martin Lázaro, Joaquín, Alfredo González Guzmán, Luis, Mar Abad García, María, Gloria Álvarez Silveiro, María, Carmen Coria Abel, María, Díaz Sánchez, Javier, Jesús Freire Regueiro, María, María Casanova Quiñoá, Ana, José Dobao Feijoo, María, Luisa Fernández Rodríguez, María, Rey Ponce, Ángela, Monte Secades, Rafael, Jesús Pérez Taboada, María, Sánchez Fernández, Rafael, Pérez Peña, Juan, Pereira, Manuel, Conde Freire, Jesús, Martínez-García, M., Bal-Alvarado, M., Santos Guerra, F., Ares-Rico, R., Suárez-Gil, R., Rodríguez-Álvarez, A., Pérez-López, A., and Casariego-Vales, E.

Published
2020
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147. Taxpayer

Author

Sanz-Gómez, Rafael, Bartolini, Antonio, editor, Cippitani, Roberto, editor, and Colcelli, Valentina, editor

Published
2019
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149. Documento de consenso sobre el diagnóstico y tratamiento de la infección bronquial crónica en la enfermedad pulmonar obstructiva crónica

Author

Javier Callejas, Francisco, Cervera Juan, Ángela, Palop Cervera, Marta, Fuster Gomila, Antonia, Marín Tapia, Alicia, Pomares Amigo, Xavier, Torres González, Mirian, Hernández Borge, Jacinto, Pérez Chica, Gerardo, Jimeno Galván, Rocío, Golpe Gómez, Rafael, Marcos Rodríguez, Pedro J., Cebollero Rivas, Pilar, Tabernero Huguet, Eva, Álvarez Martínez, Carlos, Prados Sánchez, Concha, Martínez Garcerán, José Javier, Peñalver Mellado, Carlos, García Clemente, Marta, Rodríguez López, Juan, Figueira Gonçalves, Juan Marco, José Pérez Mendoza, Guillermo, Hernández Hernández, Jesús, Amado Diago, Carlos, Pérez Giménez, Laura, Moya Álvarez, Virginia, Palou Rotger, Alexandre, Girón Moreno, Rosa, Blanco Aparicio, Marina, Navarro Rolón, Annie, Sibila, Oriol, Miravitlles Fernández, Marc, José Soler Cataluña, Juan, Alberto Fernández Villar, José, Peces-Barba Romero, Germán, de la Rosa Carrillo, David, López-Campos, José Luís, Alcázar Navarrete, Bernardino, Calle Rubio, Myriam, Cantón Moreno, Rafael, García-Rivero, Juan Luis, Máiz Carro, Luís, Olveira Fuster, Casilda, and Martínez-García, Miguel Ángel

Published
2020
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