Zobrazeno 1 - 10
of 167
pro vyhledávání: '"P. Sadrieh"'
Autor:
Kohlenberg, Leo, Horns, Leonard, Sadrieh, Frederic, Kiele, Nils, Clausen, Matthis, Ketterer, Konstantin, Navasardyan, Avetis, Czinczoll, Tamara, de Melo, Gerard, Herbrich, Ralf
Annotating large datasets can be challenging. However, crowd-sourcing is often expensive and can lack quality, especially for non-trivial tasks. We propose a method of using LLMs as few-shot learners for annotating data in a complex natural language
Externí odkaz:
http://arxiv.org/abs/2410.12470
Autor:
Xue, Tengfei, Li, Xuefeng, Azim, Tahir, Smirnov, Roman, Yu, Jianhui, Sadrieh, Arash, Pahlavan, Babak
Large language models (LLMs) have significantly improved code generation, particularly in one-pass code generation. However, most existing approaches focus solely on generating code in a single programming language, overlooking the potential of lever
Externí odkaz:
http://arxiv.org/abs/2409.04114
Retrieval-augmented generation (RAG) techniques are widely used today to retrieve and present information in a conversational format. This paper presents a set of enhancements to traditional RAG techniques, focusing on large language models (LLMs) fi
Externí odkaz:
http://arxiv.org/abs/2407.12057
Autor:
Sadrieh Hajesmaeel-Gohari, Abbas Sheikhtaheri, Fatemeh Dinari, Jamileh Farokhzadian, Kambiz Bahaadinbeigy, Khadijeh Moulaei
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Introduction mHealth apps are widely utilized in healthcare. To guarantee their usefulness and usability, it is crucial to assess them using a reliable scale tailored specifically for mHealth apps and their users. Objective The aim of this s
Externí odkaz:
https://doaj.org/article/a2392484e8ab44699b8f5836c2a615b0
Autor:
Wang, Chiao-Yi, Sadrieh, Faranguisse Kakhi, Shen, Yi-Ting, Chen, Shih-En, Kim, Sarah, Chen, Victoria, Raghavendra, Achyut, Wang, Dongyi, Saeedi, Osamah, Tao, Yang
Publikováno v:
Biomed. Opt. Express 15, 3457-3479 (2024)
The measurement of retinal blood flow (RBF) in capillaries can provide a powerful biomarker for the early diagnosis and treatment of ocular diseases. However, no single modality can determine capillary flowrates with high precision. Combining erythro
Externí odkaz:
http://arxiv.org/abs/2309.14550
Autor:
Houriyeh Ehtemam, Shabnam Sadeghi Esfahlani, Alireza Sanaei, Mohammad Mehdi Ghaemi, Sadrieh Hajesmaeel-Gohari, Rohaneh Rahimisadegh, Kambiz Bahaadinbeigy, Fahimeh Ghasemian, Hassan Shirvani
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-29 (2024)
Abstract Objective Suicide is a complex and multifactorial public health problem. Understanding and addressing the various factors associated with suicide is crucial for prevention and intervention efforts. Machine learning (ML) could enhance the pre
Externí odkaz:
https://doaj.org/article/21ebd884460e46d68aaedcf51c103ccf
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-16 (2023)
Abstract Background Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This stu
Externí odkaz:
https://doaj.org/article/5bab94b6f9104d32abb2ceb885ab1597
Akademický článek
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Publikováno v:
Journal of Caring Sciences, Vol 12, Iss 2, Pp 129-135 (2023)
Introduction: Access to healthcare services for patients with Alzheimer’s disease (AD) was limited during the COVID-19 pandemic. A mobile application (app) can help overcome this limitation for patients and caregivers. Our study aims to develop and
Externí odkaz:
https://doaj.org/article/7538932524c04e4da1ba6eac71774022
Publikováno v:
Strides in Development of Medical Education, Vol 20, Iss 1, Pp 162-172 (2023)
Background: The combined use of electronic and traditional education is called blended learning. Anatomy is a major in medical education. Using this method creates flexible learning environments and more interaction in learning.Objectives: The presen
Externí odkaz:
https://doaj.org/article/0f66459c6031437b9f220eb30dbe29a4