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pro vyhledávání: '"Pedram S"'
Needle shape, diameter, and path are critical parameters that directly affect suture depth and tissue trauma in autonomous suturing. This paper presents an optimization-based approach to specify these parameters. Given clinical suturing guidelines, a
Externí odkaz:
http://arxiv.org/abs/1901.04588
Autor:
Pedram Sodagar
Publikováno v:
پژوهشنامه مدیریت حوزه آبخیز, Vol 15, Iss 2, Pp 17-31 (2024)
Extended Abstract Background: Precipitation is one of the most critical inputs in hydrological models. Due to its significant spatiotemporal variability, high-resolution temporal and spatial data are required for accurate hydrological modeling. Preci
Externí odkaz:
https://doaj.org/article/556bd7ade28744d1815868eaf8bb68db
Autor:
Klaudia Grechuta, Pedram Shokouh, Ahmad Alhussein, Dirk Müller-Wieland, Juliane Meyerhoff, Jeremy Gilbert, Sneha Purushotham, Catherine Rolland
Publikováno v:
Interactive Journal of Medical Research, Vol 13, p e58036 (2024)
BackgroundClinical decision support systems (CDSSs) are designed to assist in health care delivery by supporting medical practice with clinical knowledge, patient information, and other relevant types of health information. CDSSs are integral parts o
Externí odkaz:
https://doaj.org/article/62905d2eb84c4a9fa2895f6fee0b55a0
Publikováno v:
Journal of Patient Safety and Risk Management. 25:123-133
Purpose As one of the leading causes of deaths and injuries, medical errors constitute a veritable threat to patient safety. Despite this fact, no unique method has yet been established to identify and evaluate medical errors. This study was conducte
Autor:
Fatemeh Pourebrahim, Nasrin Omidvar, Arezoo Rezazadeh, Hassan Eini-Zinab, Pedram Shirani, Delaram Ghodsi
Publikováno v:
BMC Geriatrics, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Food security is a function of food access and dietary diversity. Older age is a period when adequate and diverse dietary intake is a challenge. This study aimed to investigate the association between food security on the one hand
Externí odkaz:
https://doaj.org/article/1301faa19a2d4631853c49473279e122
Publikováno v:
IEEE Access, Vol 12, Pp 155295-155308 (2024)
Diagnosing brain tumors is challenging for radiologists because of the significant similarities between the tumor types. Deep learning models lack sufficient data to effectively learn the patterns of different tumors, leading adopting of transfer lea
Externí odkaz:
https://doaj.org/article/bbfd160122434afc99631cbe2201e2ee
Autor:
Hawraa Razzaq Abed Alameer, Pedram Salehpour, Seyyed Hadi Aghdasi, Mohammad-Reza Feizi-Derakhshi
Publikováno v:
IEEE Access, Vol 12, Pp 130241-130252 (2024)
Nowadays, due to individual differences and the non-stationarity properties of EEG signals, developing an accurate cross-subject EEG emotion recognition method is in demand. Despite many successful attempts, the accuracy of generalized models across
Externí odkaz:
https://doaj.org/article/f0412e1803c049a695757156ea71274f
Publikováno v:
IEEE Access, Vol 12, Pp 82146-82155 (2024)
Textual content was initially the main focus of traditional methods for detecting fake news, and these methods have yielded appointed results. However, with the exponential growth of social media platforms, there has been a significant shift towards
Externí odkaz:
https://doaj.org/article/1e7a1c080bdb4e1ea0778b131d8e8321
Autor:
Shuhan He, Paul Chong, Byung-Jun Yoon, Pei-Hung Chung, David Chen, Sammer Marzouk, Kameron C. Black, Wilson Sharp, Pedram Safari, Joshua N. Goldstein, Ali S. Raja, Jarone Lee
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in a systematic way to quantify the entropy
Externí odkaz:
https://doaj.org/article/0f4d4087776b4c5097f73f74fd9242b7
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