Applications of Artificial Bee Colony Algorithms and its Variants in Health Care

Artificial Intelligence (AI) is always in various domain of science, literature, animation, medical filed and other real world applications. AI makes the system to store large amount of data in a systematic manner and translate the information into functional tools as per the requirement of application. AI is in use for specific applications such as defense, space exploration, and medical science. The implementation of AI in healthcare is experienced through AI-based systems for more accurate and precise diagnosis, cure and treatment of debilitating conditions. Artificial Bee Colony [ABC] algorithm is a metaheuristics algorithm has been applied in various fields of health care in recent time. There are various techniques available for image processing of MRI images, noise removal techniques for EEG, ECG, EMG signals, detection of tumor, detection of breast cancer cell, all these have merits along with limitation. When these techniques are embedded with ABC algorithm their use can be extended in such a way that, they overcome their limitation and can be used in a broad domain.

[1]  Beatriz A. Garro,et al.  Classification of DNA microarrays using artificial neural networks and ABC algorithm , 2016, Appl. Soft Comput..

[2]  Satchidananda Dehuri,et al.  ABC optimized RBF network for classification of EEG signal for epileptic seizure identification , 2017 .

[3]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[4]  Anil Kumar,et al.  Adaptive filtering of EEG/ERP through Bounded Range Artificial Bee Colony (BR-ABC) algorithm , 2014, Digit. Signal Process..

[5]  K. Geetha,et al.  Quantitative Comparison of Artificial Honey Bee Colony Clustering and Enhanced SOM based K-means Clustering Algorithms for Extraction of ROI from Breast DCE-MR Images , 2013 .

[6]  Nurhan Karaboga,et al.  Adaptive filtering noisy transcranial Doppler signal by using artificial bee colony algorithm , 2013, Eng. Appl. Artif. Intell..

[7]  Amine Chikh,et al.  Design of fuzzy classifier for diabetes disease using Modified Artificial Bee Colony algorithm , 2013, Comput. Methods Programs Biomed..

[8]  Nurhan Karaboga,et al.  Elimination of noise on transcranial Doppler signal using IIR filters designed with artificial bee colony - ABC-algorithm , 2013, Digit. Signal Process..

[9]  Gerald Schaefer,et al.  CT Liver Segmentation Using Artificial Bee Colony Optimisation , 2015, KES.

[10]  Elpida T. Keravnou,et al.  AIM portraits: tracing the evolution of artificial intelligence in medicine and predicting its future in the new millennium , 2001, Artif. Intell. Medicine.

[11]  Wei-Yen Hsu,et al.  Artificial Bee Colony Algorithm for Single-Trial Electroencephalogram Analysis , 2015, Clinical EEG and neuroscience.

[12]  M. Karnan Diagnose Breast Cancer through Mammograms Using EABCO Algorithm , 2012 .

[13]  Dervis Karaboga,et al.  A survey: algorithms simulating bee swarm intelligence , 2009, Artificial Intelligence Review.

[14]  V. Tereshko,et al.  Collective Decision-Making in Honey Bee Foraging Dynamics , 2005 .

[15]  Selim Dilmac,et al.  A new ECG arrhythmia clustering method based on Modified Artificial Bee Colony algorithm, comparison with GA and PSO classifiers , 2013, 2013 IEEE INISTA.

[16]  Salim Chikhi,et al.  Artificial bees for multilevel thresholding of iris images , 2015, Swarm Evol. Comput..

[17]  Dervis Karaboga,et al.  A comprehensive survey: artificial bee colony (ABC) algorithm and applications , 2012, Artificial Intelligence Review.

[18]  Fatma Latifoglu,et al.  A novel approach to speckle noise filtering based on Artificial Bee Colony algorithm: An ultrasound image application , 2013, Comput. Methods Programs Biomed..

[19]  Peter Szolovits,et al.  The coming of age of artificial intelligence in medicine , 2009, Artif. Intell. Medicine.

[20]  Mehmet Korürek,et al.  ECG heart beat classification method based on modified ABC algorithm , 2015, Appl. Soft Comput..