Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Peyman Nejat"'
Autor:
Saghir Alfasly, PhD, Peyman Nejat, MD, Sobhan Hemati, PhD, Jibran Khan, Isaiah Lahr, Areej Alsaafin, PhD, Abubakr Shafique, PhD, Nneka Comfere, MD, Dennis Murphree, PhD, Chady Meroueh, MD, Saba Yasir, MBBS, Aaron Mangold, MD, Lisa Boardman, MD, Vijay H. Shah, MD, Joaquin J. Garcia, MD, H.R. Tizhoosh, PhD
Publikováno v:
Mayo Clinic Proceedings: Digital Health, Vol 2, Iss 1, Pp 165-174 (2024)
Objective: To assess the performance of the current foundation models in histopathology. Patients and Methods: The assessment involves a comprehensive evaluation of some foundation models, such as the CLIP derivatives, namely PLIP and BiomedCLIP, whi
Externí odkaz:
https://doaj.org/article/cde94733165d411b94e8290775eea6b9
Autor:
Peyman Nejat, Areej Alsaafin, Ghazal Alabtah, Nneka I. Comfere, Aaron R. Mangold, Dennis H. Murphree, Patricija Zot, Saba Yasir, Joaquin J. Garcia, H. R. Tizhoosh
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Patching whole slide images (WSIs) is an important task in computational pathology. While most of them are designed to classify or detect the presence of pathological lesions in a WSI, the confounding role and redundant nature of normal hist
Externí odkaz:
https://doaj.org/article/2c83a569c5024b958e63bae28d8efaf6
Autor:
Ricardo Gonzalez, Ashirbani Saha, Clinton J.V. Campbell, Peyman Nejat, Cynthia Lokker, Andrew P. Norgan
Publikováno v:
Journal of Pathology Informatics, Vol 15, Iss , Pp 100347- (2024)
This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support “Learning Health Systems” with them. Initially, the authors elaborate on these challeng
Externí odkaz:
https://doaj.org/article/1a405e680f494562b672927c3248bd2c
Autor:
Ricardo Gonzalez, Peyman Nejat, Ashirbani Saha, Clinton J.V. Campbell, Andrew P. Norgan, Cynthia Lokker
Publikováno v:
Journal of Pathology Informatics, Vol 15, Iss , Pp 100348- (2024)
Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of their generalizability. The aim of this systematic review was to assess
Externí odkaz:
https://doaj.org/article/ed85b544a79a424bb2034422e6467e53
Autor:
Borna Tadayon Najafabadi, Daniel G Rayner, Kamyar Shokraee, Kamran Shokraie, Parsa Panahi, Paravaneh Rastgou, Farnoosh Seirafianpour, Feryal Momeni Landi, Pariya Alinia, Neda Parnianfard, Nima Hemmati, Behrooz Banivaheb, Ramin Radmanesh, Saba Alvand, Parmida Shahbazi, Hojat Dehghanbanadaki, Elaheh Shaker, Kaveh Same, Esmaeil Mohammadi, Abdullah Malik, Ananya Srivastava, Peyman Nejat, Alice Tamara, Yuan Chi, Yuhong Yuan, Nima Hajizadeh, Cynthia Chan, Jamie Zhen, Dicky Tahapary, Laura Anderson, Emma Apatu, Anel Schoonees, Celeste E Naude, Lehana Thabane, Farid Foroutan
Publikováno v:
Cochrane Database of Systematic Reviews. 2023
Publikováno v:
Asian Pacific journal of cancer prevention : APJCP. 23(11)
In this article, we aimed to report the incidence rate of PC at the national and regional levels of Iran from 2014 to 2017 for the first time based on the IARC protocols.The data was recruited from the Iranian national program of cancer registry, a n
Publikováno v:
2019 27th Iranian Conference on Electrical Engineering (ICEE).
A non-linear LC resonator technique is proposed for differential-drive cross-coupled (DDCC) Rectifier's structure, with applications in efficient portable-to-portable wireless charging. The proposed circuits improved the performance for a wide range