Landmark CJ, Johannessen SI, Tomson T (2016) Dosing strategies for antiepileptic drugs: from a standard dose for all to individualised treatment by implementation of therapeutic drug monitoring. Epileptic Disord 18(4):367–383

Article  PubMed  Google Scholar 

Haddad PM, Das A, Ashfaq M, Wieck A (2009) A review of valproate in psychiatric practice. Expert Opin Drug Metab Toxicol 5(5):539–551

Article  CAS  PubMed  Google Scholar 

Li Y, Dong N, Qin YX, Dai HR, Hu YH, Zhao YT et al (2022) Therapeutic drug monitoring of perampanel in children diagnosed with epilepsy: focus on influencing factors on the plasma concentration-to-dose ratio. Epilepsia Open 7(4):737–746

Article  PubMed  PubMed Central  Google Scholar 

Yatham LN, Kennedy SH, Parikh SV, Schaffer A, Bond DJ, Frey BN et al (2018) Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) 2018 guidelines for the management of patients with bipolar disorder. Bipolar Disord 20(2):97–170

Article  PubMed  PubMed Central  Google Scholar 

Damnjanović I, Tsyplakova N, Stefanović N, Tošić T, Catić-Đorđević A, Karalis V (2023) Joint use of population pharmacokinetics and machine learning for optimizing antiepileptic treatment in pediatric population. Ther Adv Drug Saf 14:1581633561

Article  Google Scholar 

Hsu CW, Lai EC, Chen YB, Kao HY (2024) Valproic acid monitoring: serum prediction using a machine learning framework from multicenter real-world data. J Affect Disord 347:85–91

Article  CAS  PubMed  Google Scholar 

Mei S, Feng W, Zhu L, Yu Y, Yang W, Gao B et al (2017) Genetic polymorphisms and valproic acid plasma concentration in children with epilepsy on valproic acid monotherapy. Seizure 51:22–26

Article  PubMed  Google Scholar 

Mei S, Feng W, Zhu L, Li X, Yu Y, Yang W et al (2018) Effect of CYP2C19, UGT1A8, and UGT2B7 on valproic acid clearance in children with epilepsy: a population pharmacokinetic model. Eur J Clin Pharmacol 74(8):1029–1036

Article  CAS  PubMed  Google Scholar 

Hara M, Masui K, Eleveld DJ, Struys M, Uchida O (2017) Predictive performance of eleven pharmacokinetic models for propofol infusion in children for long-duration anaesthesia. Br J Anaesth 118(3):415–423

Article  CAS  PubMed  Google Scholar 

Zhang HX, Sheng CC, Liu LS, Luo B, Fu Q, Zhao Q et al (2019) Systematic external evaluation of published population pharmacokinetic models of mycophenolate mofetil in adult kidney transplant recipients co-administered with tacrolimus. Br J Clin Pharmacol 85(4):746–761

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang YL, Guilhaumou R, Blin O, Velly L, Marsot A (2020) External evaluation of population pharmacokinetic models for continuous administration of meropenem in critically ill adult patients. Eur J Clin Pharmacol 76(9):1281–1289

Article  CAS  PubMed  Google Scholar 

Wei S, Chen J, Zhao Z, Mei S (2023) External validation of population pharmacokinetic models of vancomycin in postoperative neurosurgical patients. Eur J Clin Pharmacol 79(8):1031–1042

Article  CAS  PubMed  Google Scholar 

Methaneethorn J (2018) A systematic review of population pharmacokinetics of valproic acid. Br J Clin Pharmacol 84(5):816–834

Article  PubMed  PubMed Central  Google Scholar 

Sharma A, Singh B (2020) AE-LGBM: Sequence-based novel approach to detect interacting protein pairs via ensemble of autoencoder and LightGBM. Comput Biol Med 125:103964

Article  CAS  PubMed  Google Scholar 

Gumaei A, Al-Rakhami M, Mahmoud Al Rahhal M, Raddah H Albogamy F, Al Maghayreh E, AlSalman H (2020) Prediction of COVID-19 confirmed cases using gradient boosting regression method. Comput Mater Continua 66 (1):315–329.

Yang F, Wang HZ, Mi H, Lin CD, Cai WW (2009) Using random forest for reliable classification and cost-sensitive learning for medical diagnosis. BMC Bioinformatics, 10 Suppl 1 (Suppl 1):S22.

Tike A, Tavarageri S (2017) A medical price prediction system using hierarchical decision trees.2017 IEEE International Conference on Big Data (Big Data), 3904–3913.

Takemura A, Shimizu A, Hamamoto K (2010) Discrimination of breast tumors in ultrasonic images using an ensemble classifier based on the AdaBoost algorithm with feature selection. IEEE Trans Med Imaging 29(3):598–609

Article  PubMed  Google Scholar 

Khan PW, Park S, Lee S, Byun Y, Mohammad M, Miralinaghi M (2022) Electric kickboard demand prediction in spatiotemporal dimension using clustering-aided bagging regressor. J Adv Transp 2022:1–15

Article  Google Scholar 

Sidey-Gibbons JAM,Sidey-Gibbons CJ (2019) Machine learning in medicine: a practical introduction. BMC Med Res Methodol 19(1).

Albawi S, Mohammed TA, Al-Zawi S (2017) Understanding of a convolutional neural network. International Conference on Engineering and Technology (ICET) 2017:1–6

Google Scholar 

Zhang J, Zheng Y, Qi D, Li R, Yi X (2016) DNN-based prediction model for spatio-temporal data. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPACIAL ’16). Association for Computing Machinery, NY, USA, Article 92, 1–4.

Hinton GE, Srivastava N, Krizhevsky A, Sutskever I, Salakhutdinov RR (2012) Improving neural networks by preventing co-adaptation of feature detectors. Cornell University Library arXiv.org, Ithaca

Google Scholar 

Keskar NS, Socher R (2017) Improving generalization performance by switching from Adam to SGD. Cornell University Library arXiv.org, Ithaca

Google Scholar 

Ioffe S, Szegedy C (2015) Batch normalization: accelerating deep network training by reducing internal covariate shift. Cornell University Library arXiv.org, Ithaca

Google Scholar 

Smith LN (2017) Cyclical learning rates for training neural networks. 2017 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE 464–472

Zaccara G, Messori A, Moroni F (1988) Clinical pharmacokinetics of valproic acid–1988. Clin Pharmacokinet 15(6):367–389

Article  CAS  PubMed  Google Scholar 

Klopfenstein Q, Vaiter S (2021) Linear support vector regression with linear constraints. Mach Learn 110(7):1939–1974

Article  Google Scholar 

Qamar A, Asim M, Maamar Z, Saeed S, Baker T (2022) A Quality - of - Things model for assessing the Internet - of – Things’ nonfunctional properties. Trans Emerg Telecommun Technol 33(8).

Misra S, Li H (2020) Noninvasive fracture characterization based on the classification of sonic wave travel times. Machine Learning for Subsurface Characterization 2020:243–287

Article  Google Scholar 

Buja A, Mease D, Wyner AJ (2007) Comment: Boosting algorithms: regularization, prediction and model fitting. Stat Sci 22(4).

Breiman L (1996) Bagging predictors. Mach Learn 2(24):123–140

Article  Google Scholar 

Kamiński B, Jakubczyk M, Szufel P (2018) A framework for sensitivity analysis of decision trees. Cent Eur J Oper Res 26(1):135–159

Article  PubMed  Google Scholar 

Thian YL, Ng DW, Hallinan JTPD, Jagmohan P, Sia SY, Mohamed JSA, Quek ST, Feng M (2022) Effect of training data volume on performance of convolutional neural network pneumothorax classifiers. J Digit Imaging 35(4):881–892

Article  PubMed  PubMed Central  Google Scholar 

Lustgarten JL, Gopalakrishnan V, Grover H, Visweswaran S (2008) Improving classification performance with discretization on biomedical datasets. AMIA Annu Symp Proc 2008:445–449

PubMed  PubMed Central  Google Scholar 

Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85–117

Article  PubMed  Google Scholar 

Huang S, Xu Q, Yang G, Ding J, Pei Q (2025) Machine learning for prediction of drug concentrations: application and challenges. Clin Pharmacol Ther 117(5):1236–1247

Article  CAS  PubMed  Google Scholar