Prediction of Drug Demand Based on Deep Learning Approach and Classification Model
Abstract
Keywords
Full Text:
PDFReferences
R. A. Zayed, D. Omran, and A. A. Zayed, “COVID-19 clinical and laboratory diagnosis overview,†J. Egypt. Public Health Assoc., vol. 96, no. 1, pp. 1–5, 2021.
M. Khan, M. T. Mehran, Z. U. Haq, Z. Ullah, and S. R. Naqvi, “Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review,†Expert Syst. Appl., p. 115695, 2021.
V. Reinstadler et al., “Monitoring drug consumption in Innsbruck during coronavirus disease 2019 (COVID-19) lockdown by wastewater analysis,†Sci. Total Environ., vol. 757, p. 144006, 2021.
H. A. Badreldin and B. Atallah, “Global drug shortages due to COVID-19: impact on patient care and mitigation strategies,†Res. Soc. Adm. Pharm., vol. 17, no. 1, pp. 1946–1949, 2021.
E. A. Gehrie, S. M. Frank, and S. M. Goobie, “Balancing supply and demand for blood during the COVID-19 pandemic.†Lippincott Williams & Wilkins, 2020.
R. V. G. Peddapatla et al., “Process Model Approach to Predict Tablet Weight Variability for Direct Compression Formulations at Pilot and Production Scale,†Pharmaceutics, vol. 13, no. 7, p. 1033, 2021.
Y. Ma and M. Gan, “DeepAssociate: A deep learning model exploring sequential influence and history-candidate association for sequence recommendation,†Expert Syst. Appl., vol. 185, p. 115587, 2021.
M. Gurnani, Y. Korke, P. Shah, S. Udmale, V. Sambhe, and S. Bhirud, “Forecasting of sales by using fusion of machine learning techniques,†in 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI), 2017, pp. 93–101.
A. R. B. Oglu and I. I. T. Kizi, “A method for forecasting the demand for pharmaceutical products in a distributed pharmacy network based on an integrated approach using fuzzy logic and neural networks,†in International Conference on Intelligent and Fuzzy Systems, 2020, pp. 998–1007.
S. Miller, A. El-Bahrawy, M. Dittus, M. Graham, and J. Wright, “Predicting Drug Demand with Wikipedia Views: Evidence from Darknet Markets.,†in Proceedings of the web conference 2020, 2020, pp. 2669–2675.
V. S. S. Somisetti and S. H. Palla, “Efficient Clustering of Water Distribution Network Using Affinity Propagation.,†Ingénierie des Systèmes d’Information, vol. 25, no. 4, 2020.
Y. W. Lee, J. W. Choi, and E.-H. Shin, “Machine learning model for diagnostic method prediction in parasitic disease using clinical information,†Expert Syst. Appl., p. 115658, 2021.
Y. Chang and T. Li, “Prediction Algorithm for Drugstore Consumption Members,†in 2021 IEEE 6th International Conference on Big Data Analytics (ICBDA), 2021, pp. 214–218.
A. Jozaghi et al., “Multi-model streamflow prediction using conditional bias-penalized multiple linear regression,†Stoch. Environ. Res. Risk Assess., pp. 1–19, 2021.
H. Wang, R. Czerminski, and A. C. Jamieson, “Neural networks and deep learning,†in The Machine Age of Customer Insight, Emerald Publishing Limited, 2021.
K. Abbas et al., “Application of network link prediction in drug discovery,†BMC Bioinformatics, vol. 22, no. 1, pp. 1–21, 2021.
T. S. Kumar, “Data mining based marketing decision support system using hybrid machine learning algorithm,†J. Artif. Intell., vol. 2, no. 03, pp. 185–193, 2020.
H. Wang, F. Yang, and S. Shen, “Supply Fraud Forecasting using Decision Tree Algorithm,†in 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2021, pp. 344–347.
J. Y. Ryu, H. U. Kim, and S. Y. Lee, “Deep learning improves prediction of drug–drug and drug–food interactions,†Proc. Natl. Acad. Sci., vol. 115, no. 18, pp. E4304–E4311, 2018.
W. Deelder et al., “Using deep learning to identify recent positive selection in malaria parasite sequence data,†Malar. J., vol. 20, no. 1, pp. 1–9, 2021.
A. Jha, G. Verma, Y. Khan, Q. Mehmood, D. Rebholz-Schuhmann, and R. Sahay, “Deep convolution neural network model to predict relapse in breast cancer,†in 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018, pp. 351–358.
Y. Pathak, P. K. Shukla, A. Tiwari, S. Stalin, and S. Singh, “Deep transfer learning based classification model for COVID-19 disease,†Irbm, 2020.
G. Chen and Z. Xu, “Usage of intelligent medical aided diagnosis system under the deep convolutional neural network in lumbar disc herniation,†Appl. Soft Comput., vol. 111, p. 107674, 2021.
T. A. Sipkens and S. N. Rogak, “Using k-means to identify soot aggregates in transmission electron microscopy images,†J. Aerosol Sci., vol. 152, p. 105699, 2021.
M. S. Alam et al., “Automatic human brain tumor detection in MRI image using template-based K means and improved fuzzy C means clustering algorithm,†Big Data Cogn. Comput., vol. 3, no. 2, p. 27, 2019.
Y. Hozumi, R. Wang, C. Yin, and G.-W. Wei, “UMAP-assisted K-means clustering of large-scale SARS-CoV-2 mutation datasets,†Comput. Biol. Med., vol. 131, p. 104264, 2021.
M. Yanto, S. Sanjaya, Yulasmi, D. Guswandi, and S. Arlis, “Implementation multiple linear regresion in neural network predict gold price.†Department of Informatics Engineering, Faculty of Computer Science, Universitas Putra Indonesia YPTK, Indonesia, 2021.
C. Zhou, “House price prediction using polynomial regression with Particle Swarm Optimization,†in Journal of Physics: Conference Series, 2021, vol. 1802, no. 3, p. 32034.
A. Rinaldi and Y. Devi, “Mathematical modeling for awareness, knowledge, and perception that influence willpower to pay tax using multiple regression,†in Journal of Physics: Conference Series, 2021, vol. 1796, no. 1, p. 12062.
A. A. Pishro, S. Zhang, D. Huang, F. Xiong, W. Li, and Q. Yang, “Application of artificial neural networks and multiple linear regression on local bond stress equation of UHPC and reinforcing steel bars,†Sci. Rep., vol. 11, no. 1, pp. 1–20, 2021.
B. W. Seok, K. Wee, J. Park, D. A. Kumar, and N. S. Reddy, “Modeling the teacher job satisfaction by artificial neural networks,†Soft Comput., pp. 1–13, 2021.
J. Gröhl, M. Schellenberg, K. Dreher, and L. Maier-Hein, “Deep learning for biomedical photoacoustic imaging: A review,†Photoacoustics, p. 100241, 2021.
T. M. Shah, D. P. B. Nasika, and R. Otterpohl, “Plant and Weed Identifier Robot as an Agroecological Tool Using Artificial Neural Networks for Image Identification,†Agriculture, vol. 11, no. 3, p. 222, 2021.
M. Sharma, I. Kandasamy, and V. Kandasamy, “Deep Learning for predicting neutralities in Offensive Language Identification Dataset,†Expert Syst. Appl., p. 115458, 2021.
A. Nikolopoulos, C. Samlis, M. Zeneli, N. Nikolopoulos, S. Karellas, and P. Grammelis, “Introducing an artificial neural network energy minimization multi-scale drag scheme for fluidized particles,†Chem. Eng. Sci., vol. 229, p. 116013, 2021.
K. Zaorska, P. Zawierucha, M. Świerczewska, D. Ostalska-Nowicka, J. Zachwieja, and M. Nowicki, “Prediction of steroid resistance and steroid dependence in nephrotic syndrome children,†J. Transl. Med., vol. 19, no. 1, pp. 1–13, 2021.
M. Rabiej and S. Rabiej, “Application of the artificial neural network for identification of polymers based on their X-ray diffraction curves,†Comput. Mater. Sci., vol. 186, p. 110042, 2021.
M. A. Mojid and A. B. M. Z. Hossain, “Comparative performance of multiple linear regression and artificial neural network models in estimating solute-transport parameters,†SAINS TANAH-Journal Soil Sci. Agroclimatol., vol. 18, no. 1, pp. 27–35.
G. Pappalardo, S. Cafiso, A. Di Graziano, and A. Severino, “Decision tree method to analyze the performance of lane support systems,†Sustainability, vol. 13, no. 2, p. 846, 2021.
Y. Lian, J. Chen, Z. Guan, and J. Song, “Development of a monitoring system for grain loss of paddy rice based on a decision tree algorithm,†Int. J. Agric. Biol. Eng., vol. 14, no. 1, pp. 224–229, 2021.
P. Ducange, F. Marcelloni, and R. Pecori, “Fuzzy hoeffding decision tree for data stream classification,†Int. J. Comput. Intell. Syst., vol. 14, no. 1, pp. 946–964, 2021.
V. Malik, Y. Kalakoti, and D. Sundar, “Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer,†BMC Genomics, vol. 22, no. 1, pp. 1–11, 2021.
S. Arlis and S. Defit, “Machine Learning Algorithms for Predicting the Spread of Covid‒19 in Indonesia,†2021.
S. L. Makali et al., “Comparative analysis of the health status of the population in six health zones in South Kivu: a cross-sectional population study using the WHODAS,†Confl. Health, vol. 15, no. 1, pp. 1–11, 2021.
F. S. Neves, “Correlation of the rise and fall in COVID-19 cases with the social isolation index and early outpatient treatment with hydroxychloroquine and chloroquine in the state of Santa Catarina, southern Brazil: A retrospective analysis,†Travel Med. Infect. Dis., vol. 41, p. 102005, 2021.
C. Xu, X. Chen, and L. Zhang, “Predicting river dissolved oxygen time series based on stand-alone models and hybrid wavelet-based models,†J. Environ. Manage., vol. 295, p. 113085, 2021.
S. Pokharel, P. Sah, and D. Ganta, “Improved Prediction of Total Energy Consumption and Feature Analysis in Electric Vehicles Using Machine Learning and Shapley Additive Explanations Method,†World Electr. Veh. J., vol. 12, no. 3, p. 94, 2021.
Z. Yu, S. Ye, Y. Sun, H. Zhao, and X.-Q. Feng, “Deep learning method for predicting the mechanical properties of aluminum alloys with small data sets,†Mater. Today Commun., p. 102570, 2021.
P. R. Srivastava, Z. J. Zhang, and P. Eachempati, “Deep Neural Network and Time Series Approach for Finance Systems: Predicting the Movement of the Indian Stock Market,†J. Organ. End User Comput., vol. 33, no. 5, pp. 204–226, 2021.
M. Mesgarpour et al., “Prediction of the spread of Corona-virus carrying droplets in a bus-A computational based artificial intelligence approach,†J. Hazard. Mater., vol. 413, p. 125358, 2021.
W.-J. Wang, Y. Tang, J. Xiong, and Y.-C. Zhang, “Stock market index prediction based on reservoir computing models,†Expert Syst. Appl., vol. 178, p. 115022, 2021.
S. Asvapoositkul and R. Preece, “Decision tree-based prediction model for small signal stability and generation-rescheduling preventive control,†Electr. Power Syst. Res., vol. 196, p. 107200, 2021.
DOI: http://dx.doi.org/10.18517/ijaseit.13.1.17217
Refbacks
- There are currently no refbacks.
Published by INSIGHT - Indonesian Society for Knowledge and Human Development