{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T17:47:16Z","timestamp":1773424036336,"version":"3.50.1"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1016\/j.knosys.2025.114679","type":"journal-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T07:33:32Z","timestamp":1761550412000},"page":"114679","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"special_numbering":"PC","title":["A new approach combining tangent hyperbolic and logistic sigmoid neural networks to model and solve tumor growth dynamics"],"prefix":"10.1016","volume":"330","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4306-0453","authenticated-orcid":false,"given":"Nassira","family":"Madani","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7459-2438","authenticated-orcid":false,"given":"Zakia","family":"Hammouch","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.knosys.2025.114679_bib0001","doi-asserted-by":"crossref","first-page":"2736","DOI":"10.1002\/mma.7950","article-title":"Modeling and numerical investigation of a conformable co-infection model for describing hantavirus of the European moles","volume":"45","author":"Allahamou","year":"2022","journal-title":"Math. Methods Appl. Sci"},{"issue":"4","key":"10.1016\/j.knosys.2025.114679_bib0002","doi-asserted-by":"crossref","first-page":"1953","DOI":"10.1016\/j.aej.2019.12.025","article-title":"Cancer treatment by stem cells and chemotherapy as a mathematical model with numerical simulations","volume":"59","author":"Alqudah","year":"1953","journal-title":"Alexandria Eng. J."},{"issue":"1","key":"10.1016\/j.knosys.2025.114679_bib0003","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s42600-021-00132-9","article-title":"A deep convolutional neural network for COVID-19 detection using chest X-rays","volume":"38","author":"Bassi","year":"2022","journal-title":"Res. Biomed. Eng."},{"key":"10.1016\/j.knosys.2025.114679_bib0004","first-page":"758","article-title":"A mathematical tumor growth model for exploring saturated response of M2 macrophages","volume":"88","author":"Dehingia","year":"2020","journal-title":"Healthcare Anal."},{"key":"10.1016\/j.knosys.2025.114679_bib0005","doi-asserted-by":"crossref","unstructured":"K. Dehingia, Y. Alharbi, V. Pandey, A mathematical tumor growth model for exploring saturated response of M2 macrophages, 5,100306, 2024,Elsevier.","DOI":"10.1016\/j.health.2024.100306"},{"key":"10.1016\/j.knosys.2025.114679_bib0006","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1007\/s10928-014-9386-9","article-title":"AE Modeling cancer-immune responses to therapy","volume":"41","author":"Depillis","year":"2014","journal-title":"J. Pharmacokinet. Pharmacodyn."},{"issue":"4","key":"10.1016\/j.knosys.2025.114679_bib0007","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1016\/j.jtbi.2005.06.037","article-title":"Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations","volume":"238","author":"Pillis","year":"2006","journal-title":"J. Theor. Biol."},{"issue":"1","key":"10.1016\/j.knosys.2025.114679_bib0008","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.mbs.2006.05.003","article-title":"Chemotherapy for tumors: an analysis of the dynamics and a study of quadratic and linear optimal controls","volume":"209","author":"Pillis","year":"2007","journal-title":"Math. Biosci."},{"key":"10.1016\/j.knosys.2025.114679_bib0009","series-title":"Mathematical model creation for cancer chemo-immunotherapy","first-page":"165","volume":"10","author":"Pillis","year":"2009"},{"key":"10.1016\/j.knosys.2025.114679_bib0010","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1080\/10273660108833067","article-title":"A mathematical tumor model with immune resistance and drug therapy: an optimal control approach","volume":"3","author":"Pillis","year":"2001","journal-title":"Comput. Math. Methods Med."},{"key":"10.1016\/j.knosys.2025.114679_bib0011","series-title":"The dynamics of an optimally controlled tumor model: A case study","first-page":"1221","volume":"37","author":"Pillis","year":"2003"},{"key":"10.1016\/j.knosys.2025.114679_bib0012","unstructured":"L.G. Depillis, H. Savage, Radunskaya, AE Mathematical model of colorectal cancer with monoclonal antibody treatments, arXiv preprint arXiv:1312.3023, 2013."},{"key":"10.1016\/j.knosys.2025.114679_bib0013","doi-asserted-by":"crossref","first-page":"2568","DOI":"10.1080\/00207160.2022.2074789","article-title":"Ahmet dynamical behaviour of a tumour-immune model focusing on the dosage of targeted chemotherapeutic drug","volume":"99","author":"Dhar","year":"2022","journal-title":"Int. J. Comput. Math."},{"key":"10.1016\/j.knosys.2025.114679_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127168","article-title":"A hidden multiwing memristive neural network and its application in remote sensing data security","volume":"277","author":"Ding","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.knosys.2025.114679_bib0015","series-title":"Modeling anti-tumor Th1 and Th2 immunity in the rejection of melanoma","first-page":"467","volume":"265","author":"Eftimie","year":"2010"},{"key":"10.1016\/j.knosys.2025.114679_bib0016","doi-asserted-by":"crossref","first-page":"1305","DOI":"10.1016\/j.chaos.2006.10.060","article-title":"Awad Chaos and optimal control of cancer self-remission and tumor system steady states","volume":"37","author":"El-Gohary","year":"2008","journal-title":"Chaos, Solitons Fractals"},{"key":"10.1016\/j.knosys.2025.114679_bib0017","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s12064-018-0261-x","article-title":"Mathematical modeling of cancer-immune system, considering the role of antibodies","volume":"137","author":"Ghosh","year":"2018","journal-title":"Theory Biosci."},{"issue":"6","key":"10.1016\/j.knosys.2025.114679_bib0018","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1007\/s40314-022-01990-4","article-title":"Analysis and dynamics of a mathematical model to predict unreported cases of COVID-19 epidemic in Morocco","volume":"41","author":"Hamou","year":"2022","journal-title":"Comput. Appl. Math."},{"key":"10.1016\/j.knosys.2025.114679_bib0019","doi-asserted-by":"crossref","DOI":"10.1016\/j.chaos.2022.112006","article-title":"Mathematical analysis and numerical simulation of the Ebola epidemic disease in the sense of conformable derivative","volume":"158","author":"Hammouch","year":"2022","journal-title":"Chaos, Solitons Fractals"},{"issue":"5","key":"10.1016\/j.knosys.2025.114679_bib0020","doi-asserted-by":"crossref","first-page":"1230","DOI":"10.3934\/dcdss.2024181","article-title":"Dynamics investigation and numerical simulation of fractional-order predator-prey model with Holling type II functional response","volume":"18","author":"Hammouch","year":"2025","journal-title":"Discrete Continu. Dyn. Syst. S"},{"key":"10.1016\/j.knosys.2025.114679_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.compchemeng.2020.107221","article-title":"Parameter estimation of partial differential equations using artificial neural network","volume":"147","author":"Jamili","year":"2021","journal-title":"Comput. Chem. Eng."},{"key":"10.1016\/j.knosys.2025.114679_bib0022","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s002850050127","article-title":"Modeling immunotherapy of the tumor-immune interaction","volume":"37","author":"Kirschner","year":"1998","journal-title":"J. Math. Biol."},{"issue":"12\u201313","key":"10.1016\/j.knosys.2025.114679_bib0023","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1016\/S0895-7177(00)00314-9","article-title":"Modeling tumor regrowth and immunotherapy, mathematical and computer modelling","volume":"33","author":"Kuznetsov","year":"2001","journal-title":"Math. Comput. Model."},{"key":"10.1016\/j.knosys.2025.114679_bib0024","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/BF02460644","article-title":"Alan S nonlinear dynamics of immunogenic tumors: parameter estimation and global bifurcation analysis","volume":"56","author":"Kuznetsov","year":"1994","journal-title":"Bull. Math. Biol."},{"key":"10.1016\/j.knosys.2025.114679_bib0025","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.chaos.2017.03.002","article-title":"Dynamics of a tumor-immune model considering targeted chemotherapy","volume":"98","author":"Liu","year":"2017","journal-title":"Chaos, Solitons Fractals"},{"key":"10.1016\/j.knosys.2025.114679_bib0026","doi-asserted-by":"crossref","DOI":"10.1016\/j.jocs.2025.102612","article-title":"New model of HIV\/AIDS dynamics based on Caputo-Fabrizio derivative order: optimal strategies to control the spread","volume":"90","author":"Madani","year":"2025","journal-title":"J. Comput. Sci."},{"key":"10.1016\/j.knosys.2025.114679_bib0027","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.critrevonc.2018.02.004","article-title":"Mathematical modeling of cancer metabolism","volume":"124","author":"Medina","year":"2018","journal-title":"Crit. Rev. Oncol. Hematol."},{"key":"10.1016\/j.knosys.2025.114679_bib0028","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.aej.2024.11.077","article-title":"Chaotic bifurcation dynamics in predator-prey interactions with logistic growth and Holling type-II response","volume":"115","author":"Mehdi","year":"2025","journal-title":"Alexandria Eng. J."},{"issue":"02","key":"10.1016\/j.knosys.2025.114679_bib0029","doi-asserted-by":"crossref","DOI":"10.1142\/S1793524523500924","article-title":"An SVIQR model with vaccination-age, general nonlinear incidence rate and relapse: dynamics and simulations","volume":"18","author":"Ouakka","year":"2025","journal-title":"Int. J. Biomath."},{"issue":"1","key":"10.1016\/j.knosys.2025.114679_bib0030","first-page":"233","article-title":"ANN-based methods for solving partial differential equations: a survey","volume":"29","author":"Pratama","year":"2022","journal-title":"Arab J.Basic Appl. Sci."},{"key":"10.1016\/j.knosys.2025.114679_bib0031","series-title":"Solving partial differential equations using artificial neural networks","author":"Rudd","year":"2013"},{"key":"10.1016\/j.knosys.2025.114679_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiolchem.2024.108162","article-title":"A novel radial basis neural network for the Zika virus spreading model","volume":"112","author":"Sabir","year":"2024","journal-title":"Comput. Biol. Chem."},{"key":"10.1016\/j.knosys.2025.114679_bib0033","article-title":"Mathematical modeling and bifurcation analysis of pro-and anti-tumor macrophages","volume":"5","author":"Shu","year":"2024","journal-title":"Appl. Math. Model."},{"key":"10.1016\/j.knosys.2025.114679_bib0034","series-title":"Le Machine Learning et le Deep Learning par la pratique","article-title":"Intelligence artificielle vulgaris\u00e9e","author":"Vannieuwenhuyze","year":"2019"},{"issue":"1","key":"10.1016\/j.knosys.2025.114679_bib0035","first-page":"156","article-title":"Mathematical analysis of a fractional order two strain SEIR epidemic model","volume":"7","author":"Yaagoub","year":"2024","journal-title":"Results Nonlinear Anal."},{"key":"10.1016\/j.knosys.2025.114679_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.rinp.2020.103698","article-title":"Threshold condition and non pharmaceutical interventions\u2019s control strategies for elimination of COVID-19","volume":"20","author":"Zamir","year":"2021","journal-title":"Results Phys."},{"key":"10.1016\/j.knosys.2025.114679_bib0037","series-title":"Neural Network Driven Artificial Intelligce: Decision Making Based on Fuzzy Logic","author":"Zohuri","year":"2017"}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705125017186?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705125017186?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T19:37:11Z","timestamp":1765222631000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705125017186"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":37,"alternative-id":["S0950705125017186"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2025.114679","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2025,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A new approach combining tangent hyperbolic and logistic sigmoid neural networks to model and solve tumor growth dynamics","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2025.114679","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114679"}}