Unveiling the robustness of machine learning families

Autor: R Fabra-Boluda, C Ferri, M J Ramírez-Quintana, F Martínez-Plumed

Publikováno v: Machine Learning: Science and Technology, Vol 5, Iss 3, p 035040 (2024)

The evaluation of machine learning systems has typically been limited to performance measures on clean and curated datasets, which may not accurately reflect their robustness in real-world situations where data distribution can vary from learning to

Externí odkaz: https://doaj.org/article/71fde2407280448e8ac821e20882997f

May Measurement Month 2017: an analysis of blood pressure screening results worldwide

Autor: Thomas Beaney, MRCP, Aletta E Schutte, PhD, Maciej Tomaszewski, MD, Cono Ariti, MSc, Louise M Burrell, MD, Rafael R Castillo, FPCP, Fadi J Charchar, PhD, Albertino Damasceno, PhD, Ruan Kruger, PhD, Daniel T Lackland, DrPH, Peter M Nilsson, MD, Dorairaj Prabhakaran, DM, Agustin J Ramirez, MD, Markus P Schlaich, MD, Jiguang Wang, PhD, Michael A Weber, MD, Neil R Poulter, FMed Sci, C Napiza-Granada, Ma. RC Sevilla, AA Atilano, DID Ona, A More, AP Jose, A Maheshwari, D Kondal, W Yu, W Li, S Xu, J Yu, H Zhang, B Widyantoro, Y Turana, TD Situmorang, Y Sofiatin, R Barack, H-J Lin, T-D Wang, W-J Chen, Y Sirenko, O Evstigneeva, E Negresku, ME Yousif, SA Medani, HM Beheiry, IA Ali, JM Zilberman, MJ Marin, PD Rodriguez, F Garcia-Vasquez, KE Kramoh, D Ekoua, P Lopez-Jaramillo, J Otero, G Sanchez, C Narvaez, JL Accini, R Hernandez-Hernandez, JA Octavio, I Morr, J Lopez-Rivera, D Ojji, A Arije, A Babatunte, KW Wahab, M Fernandes, SV Pereira, M Valentim, A Dzudie, S Kingue, DA Djomou Ngongang, EN Ogola, FA Barasa, B Gitura, F-T-N Malik, SR Choudhury, MA Al Mamun, VH Minh, NL Viet, S Cao Truong, C Ferri, G Parati, C Torlasco, C Borghi, FM Goma, C Syatalimi, PH Zelveian, E Barbosa, W Sebba Barroso, E Penaherrera, E Jarrin, A Yusufali, N Bazargani, B Tsinamdzgvrishvili, D Trapaidze, D Neupane, SR Mishra, J Jozwiak, J Malyszko, A Konradi, I Chazova, M Ishaq, F Memon, AM Heagerty, J Keitley, AJB Brady, JR Cockcroft, BJ McDonnell, F Lanas, Y-C Chia, H Ndhlovu, I Kiss, LM Ruilope, BF Ellenga Mbolla, AS Milhailidou, AJ Woodiwiss, S Perl, E Dolan, V Azevedo, L Garre, JG Boggia, VWY Lee, S Kowlessur, M Miglinas, D Sukackiene, RD Wainford, D Habonimana, T Masupe, J Ortellado, G Wuerzner, L Alcocer, G Burazeri, E Sanchez Delgado, D Lovic, CK Mondo, A Mostafa, SK Nadar, O Valdez Tiburcio, A Leiba, M Dorobantu, T De Backer, J Chifamba, G Stergiou, CR Nwokocha, S Sokolovic, AI Toure, KL Connell, NA Khan, D Burger, M De Carvalho Rodrigues, BK Kramer, RE Schmieder, T Unger, FS Wyss, NV Yameogo, H Beistline, JG Kenerson, B Alfonso, MH Olsen, M Soares

Publikováno v: The Lancet Global Health, Vol 6, Iss 7, Pp e736-e743 (2018)

Summary: Background: Increased blood pressure is the biggest contributor to the global burden of disease and mortality. Data suggest that less than half of the population with hypertension is aware of it. May Measurement Month was initiated to raise

Externí odkaz: https://doaj.org/article/a6638f33053b4e79affdf5d3b6c3c273

Prolonged COVID 19 Outbreak and Psychological Response of Nurses in Italian Healthcare System: Cross-Sectional Study

Autor: Jessica Ranieri, Federica Guerra, E. Perilli, Domenico Passafiume, D. Maccarone, C. Ferri, Dina Di Giacomo

Publikováno v: Frontiers in Psychology, Vol 12 (2021)

Aim of the study was to analyze the posttraumatic stress disorder risk nurses, detecting the relationship between distress experience and personality dimensions in Italian COVID-19 outbreak. A cross-sectional study was conducted based on 2 data detec

Externí odkaz: https://doaj.org/article/0183affcf1054722aa7049edddf4b77a

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