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Application of the neural net-based system of cell recognition (the Papnet System) to non-gynecologic cytologic samples
Affiliation:1. Departamento de Medicina Preventiva y Salud Pública, Universidad Autónoma de Madrid / IdiPaz, and CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain;2. Division of Geriatric Medicine, Hospital Universitario de Getafe, Madrid, Spain;1. Federal University of Piauí, Brazil;2. Federal University of Ceará, Brazil;3. University of California, Berkeley, USA;4. Lawrence Berkeley National Laboratory, USA;5. Federal University of Ouro Preto, Brazil;1. The Department of Computer Science and Engineering, Assam Engineering College, Guwahati 781013, Assam, India;2. The Department of Centre for Computational and Numerical Sciences, Institute of Advanced Study in Science and Technology, Guwahati 781035, Assam, India;3. Arya Wellness Center, Guwahati 781032, Assam, India;1. Faculty of Radiological Technology, School of Medical Sciences, Fujita Health University, Toyoake, Japan;2. School of Medicine, Fujita Health University, Toyoake, Japan;3. National Institute of Health, Maryland, United States;4. NVIDIA Corporation, Bethesda, United States;5. Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan;1. Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, China;2. Shenzhen Peng Cheng Laboratory, Shenzhen 518052, China;3. College of Computer & Information Science, Southwest University, Chongqing 400715, China;4. Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore 138632, Singapore;5. Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore 138632, Singapore
Abstract:
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