J.  Gitanjali, R.  Subhashini, 
    Enhanced Bio-Inspired Algorithm for Disease Diagnosis,
    Journal of Engineering and Applied Sciences,
    Volume 15,Issue 16,
    2020,
    Pages 3024-3031,
    ISSN 1816-949x,
    jeasci.2020.3024.3031,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2020.3024.3031)
    Abstract: Datasets are gathered for different diseases and
then the feature is extracted using dimensionality
reduction techniques. After the attributes are reduced, the
attributes are used to test and train the data using decision
tree classification algorithm techniques. The various
decision tree algorithms are also used to find the accuracy
for each diseases and then hybridization techniques are
used to solve the problem which is then used to create
upgraded yield. Metaheuristic is generally a search
algorithm which solves the optimization problems that
provides the best solution from the available solutions. It
provides a better solution with less effort compared with
other algorithms. One of the recent trend is hybrid
optimization methods. Hybridization of metaheuristics are
nothing but combining two bio-inspired algorithms. It
improves algorithmic performance in a more efficient way
to solve the problems. Hybridization techniques extracts
the strengths from the combination of each algorithm.
    Keywords: Decision tree;feature extraction;firefly algorithm;hybridization;accuracy