NOVEL HYBRID LSTBAM - BIDIRECTIONAL ASSOCIATIVE MEMORY DEEP LEARNING BASED THYROID DISEASE PREDICTION
Deep learning techniques play a vital role in the disease prediction. This research focus on the hypothyroid disease prediction using novel hybrid LSTBAM – Long Short Term Bidirectional Associative Memory based deep learning artificial neural networks prediction method. The dataset deployed has the parameters which portray the disease traits and it has 29 attributes. Results are disclosed which shows the promising enhancement.
2022-12-31 — Updated on 2022-12-31
How to Cite
D. PRIYADHARSINI, Dr. S. SASIKALA. (2022). NOVEL HYBRID LSTBAM - BIDIRECTIONAL ASSOCIATIVE MEMORY DEEP LEARNING BASED THYROID DISEASE PREDICTION . Journal of Pharmaceutical Negative Results, 1179–1185. https://doi.org/10.47750/pnr.2022.13.S10.138