no code implementations • 8 May 2024 • Mahyar Abbasian, Iman Azimi, Mohammad Feli, Amir M. Rahmani, Ramesh Jain
Agents represent one of the most emerging applications of Large Language Models (LLMs) and Generative AI, with their effectiveness hinging on multimodal capabilities to navigate complex user environments.
no code implementations • 2 May 2024 • Elahe Khatibi, Mahyar Abbasian, Zhongqi Yang, Iman Azimi, Amir M. Rahmani
This study not only shows the effectiveness of the ALCM but also underscores new research directions in leveraging the causal reasoning capabilities of LLMs.
no code implementations • 16 Mar 2024 • Zhongqi Yang, Yuning Wang, Ken S. Yamashita, Maryam Sabah, Elahe Khatibi, Iman Azimi, Nikil Dutt, Jessica L. Borelli, Amir M. Rahmani
Emotional states, as indicators of affect, are pivotal to overall health, making their accurate prediction before onset crucial.
no code implementations • 25 Feb 2024 • Kianoosh Kazemi, Iina Ryhtä, Iman Azimi, Hannakaisa Niela-Vilen, Anna Axelin, Amir M. Rahmani, Pasi Liljeberg
Our result shows that performing adequate physical activity during pregnancy and postpartum improves the QoL by units of 7. 3 and 3. 4 on average in physical health and psychological domains, respectively.
no code implementations • 18 Feb 2024 • Zhongqi Yang, Elahe Khatibi, Nitish Nagesh, Mahyar Abbasian, Iman Azimi, Ramesh Jain, Amir M. Rahmani
The personal model leverages causal discovery and inference techniques to assess personalized nutritional effects for a specific user, whereas the population model provides generalized information on food nutritional content.
no code implementations • 16 Feb 2024 • Ziyu Wang, Zhongqi Yang, Iman Azimi, Amir M. Rahmani
Mental health conditions, prevalent across various demographics, necessitate efficient monitoring to mitigate their adverse impacts on life quality.
no code implementations • 15 Feb 2024 • Mahyar Abbasian, Zhongqi Yang, Elahe Khatibi, Pengfei Zhang, Nitish Nagesh, Iman Azimi, Ramesh Jain, Amir M. Rahmani
We compare the proposed CHA with GPT4.
no code implementations • 10 Jan 2024 • Kianoosh Kazemi, Iman Azimi, Pasi Liljeberg, Amir M. Rahmani
The increasing popularity of smartwatches, equipped with various sensors including PPG, has prompted the need for a robust RR estimation method.
1 code implementation • 3 Oct 2023 • Mahyar Abbasian, Iman Azimi, Amir M. Rahmani, Ramesh Jain
openCHA includes an orchestrator to plan and execute actions for gathering information from external sources, essential for formulating responses to user inquiries.
no code implementations • 21 Sep 2023 • Mahyar Abbasian, Elahe Khatibi, Iman Azimi, David Oniani, Zahra Shakeri Hossein Abad, Alexander Thieme, Ram Sriram, Zhongqi Yang, Yanshan Wang, Bryant Lin, Olivier Gevaert, Li-Jia Li, Ramesh Jain, Amir M. Rahmani
The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare.
no code implementations • 12 Nov 2020 • Milad Asgari Mehrabadi, Seyed Amir Hossein Aqajari, Iman Azimi, Charles A Downs, Nikil Dutt, Amir M Rahmani
In contrast, vital signs (e. g., heart rate) have been utilized to early-detect different respiratory diseases in ubiquitous health monitoring.