Clinical Significance of Myocardial Injury in Patients Hospitalized for COVID-19: A Prospective, Multicenter, Cohort Study

Autor: Greenwood, J.P., McCann, G.P., Berry, C., Dweck, M., Miller, C.M., Chiribiri, A., Prasad, S., Ferreira, V.M., Bucciarelli-Ducci, C., Dawson, D., Moon, James C., Artico, Jessica, Shiwani, Hunain, Davies, Rhodri, Dweck, Marc, Berry, Colin, Roditi, Giles, Young, Robin, McConnachie, Alex, Kelly, Bernard, Macfarlane, Peter W., Miller, Christopher A., Levelt, Eylem, Goreka, Miroslawa, Somers, Kathryn, Byrom-Goulthorp, Roo J., Anderson, Michelle, Britton, Laura, Richards, Fiona, Jones, Laura M., Arnold, Ranjit, Moss, Alastair, Fisher, Jude, Wormleighton, Joanne, Parke, Kelly, Wright, Rachel, Yeo, Jian, Dawson, Dana, Falconer, Judith, Harries, Valerie, Henderson, Paula, Singh, Trisha, Newby, David, Piechnik, Stefan, Popescu, Iulia, Lukaschuk, Elena, Zhang, Qiang, Shanmuganathan, Mayooran, Neubauer, Stefan, Raman, Betty, Channon, Keith, Krasopoulos, Catherine, Nunes, Claudia, Da Silva Rodrigues, Liliana, Nixon, Harriet, Panopoulou, Athanasia, Fletcher, Alison, Manley, Peter, Mangion, Kenneth, Morrow, Andrew, Sykes, Robert, Fallon, Kirsty, Brown, Ammani, Kelly, Laura, McGinley, Christopher, Briscoe, Michael, Woodward, Rosemary, Hopkins, Tracey, McLennan, Evonne, Tynan, Nicola, Dymock, Laura, Swoboda, Peter, Wright, Judith, Exley, Donna, Steeds, Richard, Hutton, Kady, MacDonald, Sonia, Treibel, Thomas, Shetye, Abhishek, Miller, Christopher M., Orsborne, Christopher, Woodville-Jones, William, Ferguson, Susan, Bratis, Konstantinos, Fairbairn, Timothy, Sionas, Michail, Widdows, Peris, Chew, Pei Gee, Marsden, Christian, Collins, Tom, George, Linsha, Kearney, Lisa, Flett, Andrew, Smith, Simon, Zhenge, Alice, Harvey, Jake, Inacio, Liliana, Hanam-Penfold, Tomas, Gruner, Lucy, Fontana, Marianna, Razvi, Yousuf S.K., Crause, Jacolene, Davies, Nina M., Brown, James T., Chaco, Liza, Patel, Rishi, Kotecha, Tushar, Knight, Dan S., Green, Thomas, Ripley, David, Thompson, Maria, Chiribiri, Amedeo, Akerele, Ugochi, Cifra, Elna, Alskaf, Ebraham, Crawley, Richard, Villa, Adriana, Bucciarelli-Ducci, Chiara, Nightingale, Angus K., Wright, Kim, Bonnick, Esther D., Hopkins, Emma, George, Jessy, Joseph, Linta, Cole, Graham, Vimalesvaran, Kavitha, Ali, Nadine, Carr, Caitlin R., Ross, Alexandra A.R., King, Clara, Prasad, Sanjay, Farzad, Zohreh, Salmi, Sara A., Kirby, Kevin, McDiarmid, Adam, Stevenson, Hannah J., Matsvimbo, Pamela S., Joji, Lency, Fearby, Margaret, Brown, Benjamin, Bunce, Nicholas, Jennings, Robert, Sookhoo, Vennessa, Joshi, Shatabdi, Kanagala, Prathap, Fullalove, Sandra, Toohey, Catherine, Fenlon, Kate, Bellenger, Nicholas, He, Jingzhou, Statton, Sarah, Pamphilon, Nicola, Steele, Anna, Ball, Claire, McGahey, Ann, Balma, Silvia, Wilkes, Lynsey, Lewis, Katy, Walter, Michelle, Ionescu, Adrian, Ninan, Tishi, Richards, Suzanne, Williams, Marie, Alfakih, Khaled, Pilgrim, Samia, Joy, George, Manisty, Charlotte H., Hussain, Ifza, Gorecka, Miroslawa, McCann, Gerry P., Alzahir, Mohammed, Ramirez, Sara, Lin, Andrew, Swoboda, Peter P., McDiarmid, Adam K., Manisty, Charlotte, Treibel, Thomas A., Piechnik, Stefan K., Davies, Rhodri H., Ferreira, Vanessa M., Dweck, Marc R., Greenwood, John P.

Publikováno v: In JACC: Cardiovascular Imaging November 2024 17(11):1320-1331

ECG Interpretation Proficiency of Healthcare Professionals

Autor: Kashou, Anthony H., Noseworthy, Peter A., Beckman, Thomas J., Anavekar, Nandan S., Cullen, Michael W., Angstman, Kurt B., Sandefur, Benjamin J., Shapiro, Brian P., Wiley, Brandon W., Kates, Andrew M., Huneycutt, David, Braisted, Andrew, Smith, Stephen W., Baranchuk, Adrian, Grauer, Ken, O'Brien, Kevin, Kaul, Viren, Gambhir, Harvir S., Knohl, Stephen J., Albert, David, Kligfield, Paul D., Macfarlane, Peter W., Drew, Barbara J., May, Adam M.

Publikováno v: In Current Problems in Cardiology October 2023 48(10)

Automatic diagnosis of the 12-lead ECG using a deep neural network

Autor: Ribeiro, Antônio H., Ribeiro, Manoel Horta, Paixão, Gabriela M. M., Oliveira, Derick M., Gomes, Paulo R., Canazart, Jéssica A., Ferreira, Milton P. S., Andersson, Carl R., Macfarlane, Peter W., Meira Jr., Wagner, Schön, Thomas B., Ribeiro, Antonio Luiz P.

Publikováno v: Nature Communications 11, article number: 1760 (2020)

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has re

Externí odkaz: http://arxiv.org/abs/1904.01949

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Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applications

Autor: Rjoob, Khaled, Bond, Raymond, Finlay, Dewar, McGilligan, Victoria, Leslie, Stephen J., Rababah, Ali, Iftikhar, Aleeha, Guldenring, Daniel, Knoery, Charles, McShane, Anne, Peace, Aaron, Macfarlane, Peter W.

Publikováno v: In Artificial Intelligence In Medicine October 2022 132