[Retracted] An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Processor</td><td class="align_center">I7 (3.33 GHz)</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">OS</td><td class="align_center">Windows 10</td></tr><tr><td class="align_left">RAM</td><td class="align_center">16 GB</td></tr><tr><td class="align_left">Language</td><td class="align_center">Python</td></tr><tr><td class="align_left">GPU</td><td class="align_center">Geforce 1060</td></tr><tr><td class="align_left">IDE</td><td class="align_center">Spyder</td></tr><tr><td class="align_left">Generation</td><td class="align_center">8<sup>th</sup></td></tr><tr><td class="align_left">Libraries</td><td class="align_center">NumPy, TensorFlow, pandas, Keras, and scikit-learn</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Computational Intelligence and Neuroscience

tab2

Table 2

Table 2: [Retracted] An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health 