Effective Predictive Modeling for Emergency Department Visits and Evaluating Exogenous Variables Impact: Using Explainable Meta-learning Gradient Boosting

Autor: Neshat, Mehdi, Phipps, Michael, Jha, Nikhil, Khojasteh, Danial, Tong, Michael, Gandomi, Amir

Over an extensive duration, administrators and clinicians have endeavoured to predict Emergency Department (ED) visits with precision, aiming to optimise resource distribution. Despite the proliferation of diverse AI-driven models tailored for precis

Externí odkaz: http://arxiv.org/abs/2411.11275

Particle Flows for Source Localization in 3-D Using TDOA Measurements

Autor: Zhang, Wenyu, Khojasteh, Mohammad Javad, Meyer, Florian

Localization using time-difference of arrival (TDOA) has myriad applications, e.g., in passive surveillance systems and marine mammal research. In this paper, we present a Bayesian estimation method that can localize an unknown number of static sourc

Externí odkaz: http://arxiv.org/abs/2408.17096

A modified version of the PRESB preconditioner for a class of non-Hermitian complex systems of linear equations

Autor: Axelsson, Owe, Slakuyeh, Dovod Khojasteh

We present a modified version of the PRESB preconditioner for two-by-two block system of linear equations with the coefficient matrix $$\textbf{A}=\left(\begin{array}{cc} F & -G^* G & F \end{array}\right),$$ where $F\in\mathbb{C}^{n\times n}$ is Herm

Externí odkaz: http://arxiv.org/abs/2402.11184

Emulating the Human Mind: A Neural-symbolic Link Prediction Model with Fast and Slow Reasoning and Filtered Rules

Autor: Khojasteh, Mohammad Hossein, Torabian, Najmeh, Farjami, Ali, Hosseini, Saeid, Minaei-Bidgoli, Behrouz

Link prediction is an important task in addressing the incompleteness problem of knowledge graphs (KG). Previous link prediction models suffer from issues related to either performance or explanatory capability. Furthermore, models that are capable o

Externí odkaz: http://arxiv.org/abs/2310.13996

Biotransformation research advances – 2022 year in review.

Autor: Khojasteh, S. Cyrus¹ (AUTHOR) pars@gene.com, Argikar, Upendra A.² (AUTHOR), Cheruzel, Lionel¹ (AUTHOR), Cho, Sungjoon¹ (AUTHOR), Crouch, Rachel D.³ (AUTHOR), Dhaware, Deepika⁴ (AUTHOR), Heck, Carley J. S.⁵ (AUTHOR), Johnson, Kevin M.⁶ (AUTHOR), Kalgutkar, Amit S.⁷ (AUTHOR), King, Lloyd⁸ (AUTHOR), Liu, Joyce¹ (AUTHOR), Ma, Bin¹ (AUTHOR), Maw, Hlaing⁹ (AUTHOR), Miller, Grover P.¹⁰ (AUTHOR), Seneviratne, Herana Kamal¹¹ (AUTHOR), Takahashi, Ryan H.¹² (AUTHOR), Wang, Shuai¹ (AUTHOR), Wei, Cong¹³ (AUTHOR), Jackson, Klarissa D.¹⁴ (AUTHOR), McDougall, Robin (AUTHOR)

Publikováno v: Drug Metabolism Reviews. Nov2023, Vol. 55 Issue 4, p301-342. 42p.