Zobrazeno 1 - 10
of 690
pro vyhledávání: '"Sarrafzadeh, Majid"'
As Artificial Intelligence (AI) models are increasingly integrated into critical systems, the need for a robust framework to establish the trustworthiness of AI is increasingly paramount. While collaborative efforts have established conceptual founda
Externí odkaz:
http://arxiv.org/abs/2408.08448
Autor:
Ovalle, Anaelia, Goldstein, Orpaz, Kachuee, Mohammad, Wu, Elizabeth S C, Hong, Chenglin, Holloway, Ian W, Sarrafzadeh, Majid
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 4, p e22042 (2021)
BackgroundSocial media networks provide an abundance of diverse information that can be leveraged for data-driven applications across various social and physical sciences. One opportunity to utilize such data exists in the public health domain, where
Externí odkaz:
https://doaj.org/article/3c5c78d09679488f953e317dd49b1f7e
Autor:
Ramezani, Ramin, Zhang, Wenhao, Xie, Zhuoer, Shen, John, Elashoff, David, Roberts, Pamela, Stanton, Annette, Eslami, Michelle, Wenger, Neil, Sarrafzadeh, Majid, Naeim, Arash
Publikováno v:
JMIR mHealth and uHealth, Vol 7, Iss 7, p e14090 (2019)
BackgroundHealth care, in recent years, has made great leaps in integrating wireless technology into traditional models of care. The availability of ubiquitous devices such as wearable sensors has enabled researchers to collect voluminous datasets an
Externí odkaz:
https://doaj.org/article/33d1057c89c9412fa1e564c4f60d2856
Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data
Autor:
Li, Kenan, Habre, Rima, Deng, Huiyu, Urman, Robert, Morrison, John, Gilliland, Frank D, Ambite, José Luis, Stripelis, Dimitris, Chiang, Yao-Yi, Lin, Yijun, Bui, Alex AT, King, Christine, Hosseini, Anahita, Vliet, Eleanne Van, Sarrafzadeh, Majid, Eckel, Sandrah P
Publikováno v:
JMIR mHealth and uHealth, Vol 7, Iss 2, p e11201 (2019)
BackgroundTime-resolved quantification of physical activity can contribute to both personalized medicine and epidemiological research studies, for example, managing and identifying triggers of asthma exacerbations. A growing number of reportedly accu
Externí odkaz:
https://doaj.org/article/a47035c922a94672a72ed6632c7de107
Publikováno v:
EMBC 2023
Large language models have been useful in expanding mental health care delivery. ChatGPT, in particular, has gained popularity for its ability to generate human-like dialogue. However, data-sensitive domains -- including but not limited to healthcare
Externí odkaz:
http://arxiv.org/abs/2306.05552
Autor:
Fazeli, Shayan, Levine, Lionel, Beikzadeh, Mehrab, Mirzasoleiman, Baharan, Zadeh, Bita, Peris, Tara, Sarrafzadeh, Majid
Recent advances in remote health monitoring systems have significantly benefited patients and played a crucial role in improving their quality of life. However, while physiological health-focused solutions have demonstrated increasing success and mat
Externí odkaz:
http://arxiv.org/abs/2303.14267
Auditing machine learning-based (ML) healthcare tools for bias is critical to preventing patient harm, especially in communities that disproportionately face health inequities. General frameworks are becoming increasingly available to measure ML fair
Externí odkaz:
http://arxiv.org/abs/2211.08742
Analyzing and inspecting bone marrow cell cytomorphology is a critical but highly complex and time-consuming component of hematopathology diagnosis. Recent advancements in artificial intelligence have paved the way for the application of deep learnin
Externí odkaz:
http://arxiv.org/abs/2205.09880
Recent literature in self-supervised has demonstrated significant progress in closing the gap between supervised and unsupervised methods in the image and text domains. These methods rely on domain-specific augmentations that are not directly amenabl
Externí odkaz:
http://arxiv.org/abs/2108.12296