Zobrazeno 1 - 10
of 1 021
pro vyhledávání: '"Janda Monika"'
Autor:
Yan, Siyuan, Yu, Zhen, Primiero, Clare, Vico-Alonso, Cristina, Wang, Zhonghua, Yang, Litao, Tschandl, Philipp, Hu, Ming, Tan, Gin, Tang, Vincent, Ng, Aik Beng, Powell, David, Bonnington, Paul, See, Simon, Janda, Monika, Mar, Victoria, Kittler, Harald, Soyer, H. Peter, Ge, Zongyuan
Diagnosing and treating skin diseases require advanced visual skills across multiple domains and the ability to synthesize information from various imaging modalities. Current deep learning models, while effective at specific tasks such as diagnosing
Externí odkaz:
http://arxiv.org/abs/2410.15038
Autor:
Yan, Siyuan, Liu, Chi, Yu, Zhen, Ju, Lie, Mahapatra, Dwarikanath, Betz-Stablein, Brigid, Mar, Victoria, Janda, Monika, Soyer, Peter, Ge, Zongyuan
Deep learning models for medical image analysis easily suffer from distribution shifts caused by dataset artifacts bias, camera variations, differences in the imaging station, etc., leading to unreliable diagnoses in real-world clinical settings. Dom
Externí odkaz:
http://arxiv.org/abs/2401.03002
Autor:
Zegair, Fatima Al, Naranpanawa, Nathasha, Betz-Stablein, Brigid, Janda, Monika, Soyer, H. Peter, Chandra, Shekhar S.
Skin lesions known as naevi exhibit diverse characteristics such as size, shape, and colouration. The concept of an "Ugly Duckling Naevus" comes into play when monitoring for melanoma, referring to a lesion with distinctive features that sets it apar
Externí odkaz:
http://arxiv.org/abs/2309.00265
Autor:
Yan, Siyuan, Liu, Chi, Yu, Zhen, Ju, Lie, Mahapatrainst, Dwarikanath, Mar, Victoria, Janda, Monika, Soyer, Peter, Ge, Zongyuan
Skin lesion recognition using deep learning has made remarkable progress, and there is an increasing need for deploying these systems in real-world scenarios. However, recent research has revealed that deep neural networks for skin lesion recognition
Externí odkaz:
http://arxiv.org/abs/2304.01508
Autor:
Yan, Siyuan, Yu, Zhen, Zhang, Xuelin, Mahapatra, Dwarikanath, Chandra, Shekhar S., Janda, Monika, Soyer, Peter, Ge, Zongyuan
Deep neural networks have demonstrated promising performance on image recognition tasks. However, they may heavily rely on confounding factors, using irrelevant artifacts or bias within the dataset as the cue to improve performance. When a model perf
Externí odkaz:
http://arxiv.org/abs/2303.00885
Autor:
Primiero, Clare A., Rezze, Gisele Gargantini, Caffery, Liam J., Carrera, Cristina, Podlipnik, Sebastian, Espinosa, Natalia, Puig, Susana, Janda, Monika, Soyer, H. Peter, Malvehy, Josep
Publikováno v:
In Journal of Investigative Dermatology June 2024 144(6):1200-1207
Autor:
Catapan, Soraia de Camargo, Vasconcelos Silva, Carina, Bird, Dominique, Janda, Monika, Gray, Len, Maunder, Lisbeth, Clemensen, Jane, Menon, Anish, Russell, Anthony
Publikováno v:
In Canadian Journal of Diabetes June 2024 48(4):250-258
Autor:
Ackermann, Deonna M., Hersch, Jolyn K., Janda, Monika, Bracken, Karen, Turner, Robin M., Bell, Katy J.L.
Publikováno v:
In Contemporary Clinical Trials May 2024 140
Balancing the risks and benefits of sun exposure: A revised position statement for Australian adults
Autor:
Neale, Rachel E., Beedle, Victoria, Ebeling, Peter R., Elliott, Thomas, Francis, David, Girgis, Christian M., Gordon, Louisa, Janda, Monika, Jones, Graeme, Lucas, Robyn M., Mason, Rebecca S., Monnington, Philip Keith, Morahan, Julia, Paxton, Georgia, Sinclair, Craig, Shumack, Stephen, Smith, Jane, Webb, Ann R., Whiteman, David C.
Publikováno v:
In Australian and New Zealand Journal of Public Health February 2024 48(1)
Autor:
Antony, Deanna Nisha, Arenson, Ricky, Bale, Owen, Braat, Sabine, Lobo Brites, Benilda Maria, Broers, Sally, Buckle, Graham, Bukkapatnam, Sreenath, Cerni, Joanne, Chan, Doris, Collins, Michael G., Elms, Amanda, Fanning, John, Fischer, Karen, Flavell, Adam, Flicker, Leon, Furst, Chloe, Gordon, Emily H., Govindarajulu, Sridevi, Grainer, Natalie, Green, Stella Jean, Green, Suetonia C., Guha, Chandana, Hand, Samantha, Nur Hidayati, Leny Dwi, Irvine, Rachael, Ismail, Ibrahim, Jesudason, Shilpanjali, Kan, George, Kang, Ya-Yu, Kelly, Leonie, Kennedy, Debbie, Khatry, Khadija, Khelgi, Vinod, Kokoszka, Shannon, Krishnan, Anoushka, Lane, Heather, Leary, Diana, Lees, Andrea, Long, Claire, Makris, Angela, Marquez, Khalilah Katherine, Maxwell, Amanda, McGrath, Amanda, McIntyre, David, Murie, Penelope, Murphy, Karina, Chróinín, Danielle Ní, Peel, Nancye M., Xiaodan Qiu, Stephanie Polley, Rapisardi, Madeleine, Roberts, Matthew A., Roger, Simon D., Saxena, Shailly, Sen, Shaundeep, Strivens, Edward, Varghese, Julie, Waite, Louise M., Walker, Robert, Wong, Daniel, Yates, Paul Andrew, Yip, Belinda, Zaharia, Andreea, Logan, Benignus, Pascoe, Elaine M., Viecelli, Andrea K., Johnson, David W., Comans, Tracy, Hawley, Carmel M., Hickey, Laura E., Janda, Monika, Jaure, Allison, Kalaw, Emarene, Kiriwandeniya, Charani, Matsuyama, Misa, Mihala, Gabor, Nguyen, Kim-Huong, Pole, Jason D., Polkinghorne, Kevan R., Pond, Dimity, Raj, Rajesh, Reidlinger, Donna M., Scholes-Robertson, Nicole, Valks, Andrea, Wong, Germaine, Hubbard, Ruth E.
Publikováno v:
In Kidney International Reports October 2024