@article{abdulrashid_delen_usman_uzochukwu_ahmed_2024, title={A multi-objective optimization framework for determining optimal chemotherapy dosing and treatment duration}, url={http://dx.doi.org/10.1016/j.health.2024.100335}, DOI={10.1016/j.health.2024.100335}, abstractNote={Traditional randomized clinical trials are regarded as the gold standard for assessing the efficacy of chemotherapy. However, this procedure has drawbacks such as high cost, time consumption, and limited patient exploration of treatment regimens. We develop a multi-objective optimization-based framework to address these limitations and determine the best chemotherapy dosing and treatment duration. The proposed framework uses patient-specific biological parameters to create a mathematical model of cell population dynamics in the patient's body. The framework employs evolutionary heuristic search methods (simulated annealing and genetic algorithms) and a prescriptive analytics approach to optimize therapy sessions that transition from treatment to relaxation. We carefully adjust the chemotherapy dose during treatment to reduce tumor cells while preserving host cells (such as effector-immune cells). We strategically time the relaxation sessions to aid recovery, considering the ability of tumors and healthy cells to regenerate. We use a combined optimization method to determine the length of the session and the amount of drug to be administered. We compare quadratic and linear optimal control solvers for drug administration while genetic algorithms and simulated annealing are used to optimize session length. This approach is especially important in limited healthcare resources, ensuring efficient allocation while accurately identifying high-risk patients to optimize resource allocation and utilization.}, journal={Healthcare Analytics}, author={Abdulrashid, Ismail and Delen, Dursun and Usman, Basiru and Uzochukwu, Mark Izuchukwu and Ahmed, Idris}, year={2024}, month={Jun} }
 @article{usman_wang_2024, title={Attractors for Hopfield lattice model in weighted spaces}, volume={179}, ISSN={["1879-2782"]}, url={http://dx.doi.org/10.1016/j.neunet.2024.106500}, DOI={10.1016/j.neunet.2024.106500}, note={online] Available at:}, journal={NEURAL NETWORKS}, author={Usman, Basiru and Wang, Xiaoli}, year={2024}, month={Nov} }
 @article{han_kloden_usman_2020, title={Upper semi-continuous convergence of attractors for a Hopfield-type lattice model}, volume={33}, url={http://dx.doi.org/10.1088/1361-6544/ab6813}, DOI={10.1088/1361-6544/ab6813}, abstractNote={To investigate dynamical behavior of the Hopfield neural network model when its dimension becomes increasingly large, a Hopfield-type lattice system is developed as the infinite dimensional extension of the classical Hopfield model. The existence of global attractors is established for both the lattice system and its finite dimensional approximations. Moreover, the global attractors for the finite dimensional approximations are shown to converge to the attractor for the infinite dimensional lattice system upper semi-continuously.}, number={4}, journal={Nonlinearity}, author={Han, Xiaoying and Kloden, Peter E and Usman, Basiru}, year={2020}, month={Apr}, pages={1881–1906} }
 @article{han_,department of mathematics and statistics_kloeden_usman_2019, title={Long term behavior of a random Hopfield neural lattice model}, url={http://dx.doi.org/10.3934/cpaa.2019039}, DOI={10.3934/cpaa.2019039}, abstractNote={A Hopfield neural lattice model is developed as the infinite dimensional extension of the classical finite dimensional Hopfield model. In addition, random external inputs are considered to incorporate environmental noise. The resulting random lattice dynamical system is first formulated as a random ordinary differential equation on the space of square summable bi-infinite sequences. Then the existence and uniqueness of solutions, as well as long term dynamics of solutions are investigated.}, journal={Communications on Pure & Applied Analysis}, author={Han, Xiaoying and ,Department of Mathematics and Statistics, Auburn University and Kloeden, Peter E. and Usman, Basiru}, year={2019} }
 @article{chidume_bello_usman_2015, title={Krasnoselskii-type algorithm for zeros of strongly monotone Lipschitz maps in classical banach spaces}, volume={4}, url={http://dx.doi.org/10.1186/s40064-015-1044-1}, DOI={10.1186/s40064-015-1044-1}, abstractNote={Let [Formula: see text], [Formula: see text], and [Formula: see text] be a strongly monotone and Lipschitz mapping. A Krasnoselskii-type sequence is constructed and proved to converge strongly to the unique solution of [Formula: see text]. Furthermore, our technique of proo f is of independent interest.}, journal={SpringerPlus}, author={Chidume, C E and Bello, A U and Usman, B}, year={2015}, month={Dec}, pages={297} }