"In the present time, biomedical data processing is an important step in the process of diagnostics, prevention and healthcare in the physicians work. The goal of this work is to help the physicians to cope with long-term biomedical data. In present time, many optimization, classification and data processing methods are inspired by nature. This paper reviews most recent advances on the field of ant colony inspired clustering. With constantly growing datasets needed to be processed, there is a significant need to study and implement robust and effective methods for processing such datasets. Thus, improved methods are presented and evaluated on long-term ECG data recordings. Paper also concentrates on the drawbacks and advantages of the methods. This paper also presents and evaluates novel method called ACO\\_DTree for classification tree generation and their evolution inspired by natural processes." . . . "Advaced Topics in Scattering and Biomedical Engineering" . . . . "Veylep\u0161en\u00E9 algoritmy inspirovan\u00E9 mraven\u010D\u00EDmi koloniemi p\u0159i zpracov\u00E1n\u00ED biomedic\u00EDnsk\u00FDch dat"@cs . . "Improved Ant Colony Inspired Algorithms in Biomedical Data Processing" . . "21230" . "ACO_DTree; ant colony clustering; ant colony optimization; dynamic time warping"@en . "RIV/68407700:21230/08:03145519!RIV09-MSM-21230___" . "In the present time, biomedical data processing is an important step in the process of diagnostics, prevention and healthcare in the physicians work. The goal of this work is to help the physicians to cope with long-term biomedical data. In present time, many optimization, classification and data processing methods are inspired by nature. This paper reviews most recent advances on the field of ant colony inspired clustering. With constantly growing datasets needed to be processed, there is a significant need to study and implement robust and effective methods for processing such datasets. Thus, improved methods are presented and evaluated on long-term ECG data recordings. Paper also concentrates on the drawbacks and advantages of the methods. This paper also presents and evaluates novel method called ACO\\_DTree for classification tree generation and their evolution inspired by natural processes."@en . "Improved Ant Colony Inspired Algorithms in Biomedical Data Processing"@en . "World Scientific" . "[F34AE1DC477D]" . "Lhotsk\u00E1, Lenka" . "8"^^ . "371683" . . . . . . "Veylep\u0161en\u00E9 algoritmy inspirovan\u00E9 mraven\u010D\u00EDmi koloniemi p\u0159i zpracov\u00E1n\u00ED biomedic\u00EDnsk\u00FDch dat"@cs . . "3"^^ . . . "3"^^ . "2007-09-28+02:00"^^ . "Improved Ant Colony Inspired Algorithms in Biomedical Data Processing" . "\u00DA\u010Delem t\u00E9to pr\u00E1ce je poskytnout pomoc l\u00E9ka\u0159\u016Fm, kte\u0159\u00ED pracuj\u00ED s dlouhodob\u00FDmi biomedicinsk\u00FDmi z\u00E1znamy. K dispozici je velk\u00E9 mno\u017Estv\u00ED algoritm\u016F inspirovan\u00FDch p\u0159\u00EDrodn\u00EDmi procesy. Pr\u00E1ce uv\u00E1d\u00ED n\u011Bkter\u00E9 vylep\u0161en\u00E9 metody a jejich aplikaci na dlouhodob\u00E9 z\u00E1znamy EKG. Uv\u00E1d\u00EDme i novou metodu ACO_DTree, kter\u00E1 slou\u017E\u00ED k vytv\u00E1\u0159en\u00ED rozhodovac\u00EDch strom\u016F a jejich optimalizaci."@cs . "Singapore" . "Improved Ant Colony Inspired Algorithms in Biomedical Data Processing"@en . "Z(MSM6840770012)" . "Huptych, Michal" . . "978-981-281-484-5" . . "RIV/68407700:21230/08:03145519" . . "Lefkada" . . "Bur\u0161a, Miroslav" .