Zobrazeno 1 - 10
of 693
pro vyhledávání: '"Sarrafzadeh Majid"'
Autor:
Oskouie, Haniyeh Ehsani, Chance, Christina, Huang, Claire, Capetz, Margaret, Eyeson, Elizabeth, Sarrafzadeh, Majid
Content moderation and toxicity classification represent critical tasks with significant social implications. However, studies have shown that major classification models exhibit tendencies to magnify or reduce biases and potentially overlook or disa
Externí odkaz:
http://arxiv.org/abs/2411.17876
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
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
Autor:
Fazeli, Shayan, Sarrafzadeh, Majid
Topic Modeling refers to the problem of discovering the main topics that have occurred in corpora of textual data, with solutions finding crucial applications in numerous fields. In this work, inspired by the recent advancements in the Natural Langua
Externí odkaz:
http://arxiv.org/abs/2108.08946
Intracranial hemorrhage occurs when blood vessels rupture or leak within the brain tissue or elsewhere inside the skull. It can be caused by physical trauma or by various medical conditions and in many cases leads to death. The treatment must be star
Externí odkaz:
http://arxiv.org/abs/2105.05891