Search Results - "Martínez Roldan, Jordi"

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis by Hardy-Werbin, Max, Maiques, José Maria, Busto, Marcos, Cirera, Isabel, Aguirre, Alfons, Garcia-Gisbert, Nieves, Zuccarino, Flavio, Carbullanca, Santiago, Del Carpio, Luis Alexander, Ramal, Didac, Gayete, Ángel, Martínez-Roldan, Jordi, Marquez-Colome, Albert, Bellosillo, Beatriz, Gibert, Joan

“…The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextension of healthcare. Both Chest X-rays (CXR) and blood test…”
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Exploring the Association of Cancer and Depression in Electronic Health Records: Combining Encoded Diagnosis and Mining Free-Text Clinical Notes by Leis, Angela, Casadevall, David, Albanell, Joan, Posso, Margarita, Macià, Francesc, Castells, Xavier, Ramírez-Anguita, Juan Manuel, Martínez Roldán, Jordi, Furlong, Laura I, Sanz, Ferran, Ronzano, Francesco, Mayer, Miguel A

“…Background: A cancer diagnosis is a source of psychological and emotional stress, which are often maintained for sustained periods of time that may lead to…”
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The Prescription of Mobile Apps by Primary Care Teams: A Pilot Project in Catalonia by Lopez Segui, Francesc, Pratdepadua Bufill, Carme, Abdon Gimenez, Nuria, Martinez Roldan, Jordi, Garcia Cuyas, Francesc

“…In Catalonia, the Fundació TIC Salut Social's mHealth Office created the AppSalut Site to showcase to mobile apps in the field of health and social services…”
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The big data era: The usefulness of folksonomy for natural language processing by Sans, Laia, Vallvé, Ismael, Teixidó, Joan, Picas, Josep Manel, Martínez-Roldán, Jordi, Pascual, Julio

“…A huge amount of clinical data is generated daily and it is usually filed in clinical reports as natural language. Data extraction and further analysis…”
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Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension: a multinational cohort study by Reyes, Carlen, Pistillo, Andrea, Fernández-Bertolín, Sergio, Recalde, Martina, Roel, Elena, Puente, Diana, Sena, Anthony G, Blacketer, Clair, Lai, Lana, Alshammari, Thamir M, Ahmed, Waheed-UI-Rahman, Alser, Osaid, Alghoul, Heba, Areia, Carlos, Dawoud, Dalia, Prats-Uribe, Albert, Valveny, Neus, de Maeztu, Gabriel, Sorlí Redó, Luisa, Martinez Roldan, Jordi, Lopez Montesinos, Inmaculada, Schilling, Lisa M, Golozar, Asieh, Reich, Christian, Posada, Jose D, Shah, Nigam, You, Seng Chan, Lynch, Kristine E, DuVall, Scott L, Matheny, Michael E, Nyberg, Fredrik, Ostropolets, Anna, Hripcsak, George, Rijnbeek, Peter R, Suchard, Marc A, Ryan, Patrick, Kostka, Kristin, Duarte-Salles, Talita

“…ObjectiveTo characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients.Design…”
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La era del big data: análisis del lenguaje natural mediante la aplicación de folksonomía by Sans, Laia, Vallvé, Ismael, Teixidó, Joan, Picas, Josep Manel, Martínez-Roldán, Jordi, Pascual, Julio

“…Gran parte de la información médica que se deriva de la práctica clínica habitual queda recogida en forma de lenguaje natural en los informes médicos…”
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Prescription and Integration of Accredited Mobile Apps in Catalan Health and Social Care: Protocol for the AppSalut Site Design by López Seguí, Francesc, Pratdepàdua Bufill, Carme, Rius Soler, Ariadna, de San Pedro, Marc, López Truño, Bernat, Aguiló Laine, Agnès, Martínez Roldán, Jordi, García Cuyàs, Francesc

“…The use of new mobile technologies in the health and social welfare sectors is already a reality. The ICT Social Health Foundation, in accordance with the…”
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Digital health as a motor for change towards new healthcare models and the relationship between patients and healthcare professionals. Disruption of healthcare processes by Garcia-Cuyàs, Francesc, de San Pedro, Marc, Martínez Roldan, Jordi

“…We find ourselves at the end of an era of asymmetry in the domain of health information where the majority of this data is in the hands of the healthcare…”
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Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS by Kostka, Kristin, Duarte-Salles, Talita, Prats-Uribe, Albert, Sena, Anthony G, Pistillo, Andrea, Khalid, Sara, Lai, Lana Y H, Golozar, Asieh, Alshammari, Thamir M, Dawoud, Dalia M, Nyberg, Fredrik, Wilcox, Adam B, Andryc, Alan, Williams, Andrew, Ostropolets, Anna, Areia, Carlos, Jung, Chi Young, Harle, Christopher A, Reich, Christian G, Blacketer, Clair, Morales, Daniel R, Dorr, David A, Burn, Edward, Roel, Elena, Tan, Eng Hooi, Minty, Evan, DeFalco, Frank, de Maeztu, Gabriel, Lipori, Gigi, Alghoul, Hiba, Zhu, Hong, Thomas, Jason A, Bian, Jiang, Park, Jimyung, Martínez Roldán, Jordi, Posada, Jose D, Banda, Juan M, Horcajada, Juan P, Kohler, Julianna, Shah, Karishma, Natarajan, Karthik, Lynch, Kristine E, Liu, Li, Schilling, Lisa M, Recalde, Martina, Spotnitz, Matthew, Gong, Mengchun, Matheny, Michael E, Valveny, Neus, Weiskopf, Nicole G, Shah, Nigam, Alser, Osaid, Casajust, Paula, Park, Rae Woong, Schuff, Robert, Seager, Sarah, DuVall, Scott L, You, Seng Chan, Song, Seokyoung, Fernández-Bertolín, Sergio, Fortin, Stephen, Magoc, Tanja, Falconer, Thomas, Subbian, Vignesh, Huser, Vojtech, Ahmed, Waheed-Ul-Rahman, Carter, William, Guan, Yin, Galvan, Yankuic, He, Xing, Rijnbeek, Peter R, Hripcsak, George, Ryan, Patrick B, Suchard, Marc A, Prieto-Alhambra, Daniel

“…Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the…”
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Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort study by Voss, Erica A., Shoaibi, Azza, Yin Hui Lai, Lana, Blacketer, Clair, Alshammari, Thamir, Makadia, Rupa, Haynes, Kevin, Sena, Anthony G., Rao, Gowtham, van Sandijk, Sebastiaan, Fraboulet, Clement, Boyer, Laurent, Le Carrour, Tanguy, Horban, Scott, Morales, Daniel R., Martínez Roldán, Jordi, Ramírez-Anguita, Juan Manuel, Mayer, Miguel A., de Wilde, Marcel, John, Luis H., Duarte-Salles, Talita, Roel, Elena, Pistillo, Andrea, Kolde, Raivo, Maljković, Filip, Denaxas, Spiros, Papez, Vaclav, Kahn, Michael G., Natarajan, Karthik, Reich, Christian, Secora, Alex, Minty, Evan P., Shah, Nigam H., Posada, Jose D., Garcia Morales, Maria Teresa, Bosca, Diego, Cadenas Juanino, Honorio, Diaz Holgado, Antonio, Pedrera Jiménez, Miguel, Serrano Balazote, Pablo, García Barrio, Noelia, Şen, Selçuk, Üresin, Ali Yağız, Erdogan, Baris, Belmans, Luc, Byttebier, Geert, Malbrain, Manu L.N.G., Dedman, Daniel J., Cuccu, Zara, Vashisht, Rohit, Butte, Atul J., Patel, Ayan, Dahm, Lisa, Han, Cora, Bu, Fan, Arshad, Faaizah, Ostropolets, Anna, Nyberg, Fredrik, Hripcsak, George, Suchard, Marc A., Prieto-Alhambra, Dani, Rijnbeek, Peter R., Schuemie, Martijn J., Ryan, Patrick B.

“…Adverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with the vaccines,…”
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Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort studyResearch in context by Erica A. Voss, Azza Shoaibi, Lana Yin Hui Lai, Clair Blacketer, Thamir Alshammari, Rupa Makadia, Kevin Haynes, Anthony G. Sena, Gowtham Rao, Sebastiaan van Sandijk, Clement Fraboulet, Laurent Boyer, Tanguy Le Carrour, Scott Horban, Daniel R. Morales, Jordi Martínez Roldán, Juan Manuel Ramírez-Anguita, Miguel A. Mayer, Marcel de Wilde, Luis H. John, Talita Duarte-Salles, Elena Roel, Andrea Pistillo, Raivo Kolde, Filip Maljković, Spiros Denaxas, Vaclav Papez, Michael G. Kahn, Karthik Natarajan, Christian Reich, Alex Secora, Evan P. Minty, Nigam H. Shah, Jose D. Posada, Maria Teresa Garcia Morales, Diego Bosca, Honorio Cadenas Juanino, Antonio Diaz Holgado, Miguel Pedrera Jiménez, Pablo Serrano Balazote, Noelia García Barrio, Selçuk Şen, Ali Yağız Üresin, Baris Erdogan, Luc Belmans, Geert Byttebier, Manu L.N.G. Malbrain, Daniel J. Dedman, Zara Cuccu, Rohit Vashisht, Atul J. Butte, Ayan Patel, Lisa Dahm, Cora Han, Fan Bu, Faaizah Arshad, Anna Ostropolets, Fredrik Nyberg, George Hripcsak, Marc A. Suchard, Dani Prieto-Alhambra, Peter R. Rijnbeek, Martijn J. Schuemie, Patrick B. Ryan

“…Background: Adverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with…”
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