Zobrazeno 1 - 10
of 1 413
pro vyhledávání: '"Aalami A"'
Autor:
Zagar, Philipp, Ravi, Vishnu, Aalami, Lauren, Krusche, Stephan, Aalami, Oliver, Schmiedmayer, Paul
The ability of large language models (LLMs) to transform, interpret, and comprehend vast quantities of heterogeneous data presents a significant opportunity to enhance data-driven care delivery. However, the sensitive nature of protected health infor
Externí odkaz:
http://arxiv.org/abs/2408.04680
Publikováno v:
Journal of Horticultural Research, Vol 27, Iss 1, Pp 37-46 (2019)
Iran is one of the main diversity centers and origins of pistachios in the world. Pistachio cultivation spread first within the ancient Persian Empire and then moved gradually westward. Knowledge of the genetic relationships among wild and cultivated
Externí odkaz:
https://doaj.org/article/056dd2b5b8504fefbc566f189884de43
Autor:
Zakka, Cyril, Cho, Joseph, Fahed, Gracia, Shad, Rohan, Moor, Michael, Fong, Robyn, Kaur, Dhamanpreet, Ravi, Vishnu, Aalami, Oliver, Daneshjou, Roxana, Chaudhari, Akshay, Hiesinger, William
Clinicians spend large amounts of time on clinical documentation, and inefficiencies impact quality of care and increase clinician burnout. Despite the promise of electronic medical records (EMR), the transition from paper-based records has been nega
Externí odkaz:
http://arxiv.org/abs/2405.07896
Autor:
Rao, Adrit, Fisher, Andrea, Chang, Ken, Panagides, John Christopher, McNamara, Katherine, Lee, Joon-Young, Aalami, Oliver
Data augmentations are widely used in training medical image deep learning models to increase the diversity and size of sparse datasets. However, commonly used augmentation techniques can result in loss of clinically relevant information from medical
Externí odkaz:
http://arxiv.org/abs/2404.10965
Autor:
Schmiedmayer, Paul, Rao, Adrit, Zagar, Philipp, Ravi, Vishnu, Zahedivash, Aydin, Fereydooni, Arash, Aalami, Oliver
Objective: To enhance health literacy and accessibility of health information for a diverse patient population by developing a patient-centered artificial intelligence (AI) solution using large language models (LLMs) and Fast Healthcare Interoperabil
Externí odkaz:
http://arxiv.org/abs/2402.01711
Software engineering for digital health applications entails several challenges, including heterogeneous data acquisition, data standardization, software reuse, security, and privacy considerations. We explore these challenges and how our Stanford Sp
Externí odkaz:
http://arxiv.org/abs/2311.03363
The clinical explainability of convolutional neural networks (CNN) heavily relies on the joint interpretation of a model's predicted diagnostic label and associated confidence. A highly certain or uncertain model can significantly impact clinical dec
Externí odkaz:
http://arxiv.org/abs/2308.11902
Autor:
Aalami, Amir Hossein, Abdeahad, Hossein, Aalami, Farnoosh, Sathyapalan, Thozhukat, Sahebkar, Amirhossein
Publikováno v:
In Clinical Biochemistry August 2024 130
Autor:
Fatemeh Mohammadzadeh, Ali Delshad Noughabi, Sina Sabeti Bilondi, Mitra Tavakolizadeh, Jafar Hajavi, Hosein Aalami, Mohsen Sahebanmaleki
Publikováno v:
Journal of Research & Health, Vol 14, Iss 3, Pp 217-230 (2024)
Background: The recent novel coronavirus disease 2019 (COVID-19) pandemic has underlined the importance of risk score models in public health emergencies. This study aimed to develop a risk prediction score to identify high-risk hospitalized patients
Externí odkaz:
https://doaj.org/article/9a102a446edd4e8e8e5374579027c913
This paper presents a novel multi-objective formulation to investigate optimal shape of double curvature arch dams in dam-reservoir systems considering its volume and natural frequencies. For this purpose, multi-objective charge system search algorit
Externí odkaz:
http://arxiv.org/abs/2208.12920