An Improved Multimodal Combination Deep Learning Neural System for Classifying Lung Malignancy

As one of the primary foundations of demise globally, malignancy demands ongoing improvements in initial detection and care. In the realm of medicinal image exploration, Deep Learning (DL) a subclass of artificial intelligence has become a potent tool that is transforming the detection and diagnosis of cancer. The study highlights the distinct difficulties that each area presents as it examines the several modalities used in lung cancer diagnosis, including clinical data, genetics, and medical imaging (such as radiology and pathology). The Multimodal Mixture Deep Neural Network (MMDNN) makes a major advancement in medical artificial intelligence with its remarkable 92.5% accuracy rate. MMDNN has exceptional sensitivity and specificity are 98.15%, 97.49%. The results are compared to well-known techniques like as CNN, DNN, and Res-Net. According to the findings, MMDNN will play a decisive part in transforming the diagnosis of lung malignancy by enabling quicker and more precise documentation of this serious illness.