Utilization of Different Machine Learning Techniques on Anti-cancer Plant Leaves Data

Cancer a leading cause of death globally, now demanding new therapies and methodologies which give efficient therapeutic effect with minimal side effects. Kingdom plantae is rich source, as is abundant with members of great significant use. On going research on plant driven therapies Particularly “leaves “of few plants are proved by experimentations to be enriched with constituents which proves to be a great remedy to pathologies like cancer. The review serves an overview of anti-cancerous property identified by multiple researchers on the leave extracts of plants such as – Mint, Neem, Oleander, Parijat and Peepal. Ethyl extract of Mentha piperita (Mint)leaves shows inhibitory effect on cancer cell lines. Apoptosis is found to be induced by leafy extract of Azadirachta indica (Neem). Water leaf extract of Nerium oleander (Oleander) was clinically found to hamper lung cancer activity. The methanolic extract of Nyctanthes arbortristis (Parijat) inhibit cancer cell lines.The leaves ethanolic extract of Ficus religiosa (Peepal) inhibit adenocarcinoma. ResNet50 Feature extractor was used for Random Forest, Adaboost, XG Boost, and classification tree algorithms. Using Random Forest and Gradient Boosting (XGBoost), the highest accuracy of 98.4% with ResNet50 feature extractor was achieved.