Prediction of seasonal infectious diseases based on hybrid machine learning approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15929-2.pdf
Reference19 articles.
1. Arquam M, Singh A, Cherifi H (2020) Impact of seasonal condition on vector-borne epidemiological dynamics. IEEE Access 8:94510–94525
2. Bhatnagar S, Lal V, Gupta SD, Gupta OP (2012) Forecasting incidences of dengue in Rajasthan, using time series analyses. Indian J Public Health 56(4):281
3. Davi C et al (2019) Severe dengue prognosis using human genome data and machine learning. IEEE Trans on Biomed Eng 66(10):2861–2868
4. Dutta P, Paul S, Obaid AJ, Pal S, Mukhopadhyay K (2021) Feature selections based artificial intelligence technique for the predictions of COVID like diseases. J Phys Conf Ser 1963(1):012167
5. Gambhir S, Malik SK, Kumar Y (2017) PSO-ANN based diagnostics model for the early detections of dengue diseases. New Horizons Transl Med 4(1–4):1–8
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