Biomedical data classification has become a hot research topic in recent years,thanks to the latest technological advancements made in healthcare.Biome-dical data is usually examined by physicians for decision making ...Biomedical data classification has become a hot research topic in recent years,thanks to the latest technological advancements made in healthcare.Biome-dical data is usually examined by physicians for decision making process in patient treatment.Since manual diagnosis is a tedious and time consuming task,numerous automated models,using Artificial Intelligence(AI)techniques,have been presented so far.With this motivation,the current research work presents a novel Biomedical Data Classification using Cat and Mouse Based Optimizer with AI(BDC-CMBOAI)technique.The aim of the proposed BDC-CMBOAI technique is to determine the occurrence of diseases using biomedical data.Besides,the proposed BDC-CMBOAI technique involves the design of Cat and Mouse Optimizer-based Feature Selection(CMBO-FS)technique to derive a useful subset of features.In addition,Ridge Regression(RR)model is also utilized as a classifier to identify the existence of disease.The novelty of the current work is its designing of CMBO-FS model for data classification.Moreover,CMBO-FS technique is used to get rid of unwanted features and boosts the classification accuracy.The results of the experimental analysis accomplished by BDC-CMBOAI technique on benchmark medical dataset established the supremacy of the proposed technique under different evaluation measures.展开更多
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R203)Princess Nourah bint Abdulrahman University,Riyadh,Saudi ArabiaThe authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4340237DSR03.
文摘Biomedical data classification has become a hot research topic in recent years,thanks to the latest technological advancements made in healthcare.Biome-dical data is usually examined by physicians for decision making process in patient treatment.Since manual diagnosis is a tedious and time consuming task,numerous automated models,using Artificial Intelligence(AI)techniques,have been presented so far.With this motivation,the current research work presents a novel Biomedical Data Classification using Cat and Mouse Based Optimizer with AI(BDC-CMBOAI)technique.The aim of the proposed BDC-CMBOAI technique is to determine the occurrence of diseases using biomedical data.Besides,the proposed BDC-CMBOAI technique involves the design of Cat and Mouse Optimizer-based Feature Selection(CMBO-FS)technique to derive a useful subset of features.In addition,Ridge Regression(RR)model is also utilized as a classifier to identify the existence of disease.The novelty of the current work is its designing of CMBO-FS model for data classification.Moreover,CMBO-FS technique is used to get rid of unwanted features and boosts the classification accuracy.The results of the experimental analysis accomplished by BDC-CMBOAI technique on benchmark medical dataset established the supremacy of the proposed technique under different evaluation measures.
