Zobrazeno 1 - 10
of 2 609
pro vyhledávání: '"Hassanpour P"'
Artificial intelligence (AI) has rapidly transformed various sectors, including healthcare, where it holds the potential to revolutionize clinical practice and improve patient outcomes. However, its integration into medical settings brings significan
Externí odkaz:
http://arxiv.org/abs/2412.03576
Autor:
Hosseini, Pedram, Sin, Jessica M., Ren, Bing, Thomas, Bryceton G., Nouri, Elnaz, Farahanchi, Ali, Hassanpour, Saeed
There is a lack of benchmarks for evaluating large language models (LLMs) in long-form medical question answering (QA). Most existing medical QA evaluation benchmarks focus on automatic metrics and multiple-choice questions. While valuable, these ben
Externí odkaz:
http://arxiv.org/abs/2411.09834
Handling implicit language is essential for natural language processing systems to achieve precise text understanding and facilitate natural interactions with users. Despite its importance, the absence of a metric for accurately measuring the implici
Externí odkaz:
http://arxiv.org/abs/2411.05172
Autor:
Das, Amit, Shukla, Tanmay, Tomita, Naofumi, Richards, Ryland, Vidis, Laura, Ren, Bing, Hassanpour, Saeed
Grading inflammatory bowel disease (IBD) activity using standardized histopathological scoring systems remains challenging due to resource constraints and inter-observer variability. In this study, we developed a deep learning model to classify activ
Externí odkaz:
http://arxiv.org/abs/2410.19690
Autor:
Jiang, Shuai, Robinson, Christina, Anderson, Joseph, Hisey, William, Butterly, Lynn, Suriawinata, Arief, Hassanpour, Saeed
Colonoscopy screening is an effective method to find and remove colon polyps before they can develop into colorectal cancer (CRC). Current follow-up recommendations, as outlined by the U.S. Multi-Society Task Force for individuals found to have polyp
Externí odkaz:
http://arxiv.org/abs/2410.09880
Autor:
McMahon, Jack, Tomita, Naofumi, Tatishev, Elizabeth S., Workman, Adrienne A., Costales, Cristina R, Banaei, Niaz, Martin, Isabella W., Hassanpour, Saeed
This study introduces a new framework for the artificial intelligence-assisted characterization of Gram-stained whole-slide images (WSIs). As a test for the diagnosis of bloodstream infections, Gram stains provide critical early data to inform patien
Externí odkaz:
http://arxiv.org/abs/2409.15546
Autor:
Jiang, Liyao, Hassanpour, Negar, Salameh, Mohammad, Singamsetti, Mohan Sai, Sun, Fengyu, Lu, Wei, Niu, Di
Text-to-image (T2I) diffusion models have demonstrated impressive capabilities in generating high-quality images given a text prompt. However, ensuring the prompt-image alignment remains a considerable challenge, i.e., generating images that faithful
Externí odkaz:
http://arxiv.org/abs/2408.11706
The effective planning and allocation of resources in modern breeding programs is a complex task. Breeding program design and operational management have a major impact on the success of a breeding program and changing parameters such as the number o
Externí odkaz:
http://arxiv.org/abs/2407.17286
Lip-based biometric authentication (LBBA) has attracted many researchers during the last decade. The lip is specifically interesting for biometric researchers because it is a twin biometric with the potential to function both as a physiological and a
Externí odkaz:
http://arxiv.org/abs/2407.08717
This paper introduces a novel method of Progressive Low Rank Decomposition (PLRD) tailored for the compression of large language models. Our approach leverages a pre-trained model, which is then incrementally decompressed to smaller sizes using progr
Externí odkaz:
http://arxiv.org/abs/2406.19995