Тиббий тимсолларни аниқлашда синфлаштириш масаласини ечишнинг баҳоларни ҳисоблашга асосланган усул ва алгоритмлари
Аннотация
Мақолада тиббий тимсолларни аниқлашнинг синфлаштириш масаласини ечишда баҳоларни ҳисоблаш
алгоритмларига асосланган усул ва дастурий таъминоти ишлаб чиқилган. Дастурий таъминот ташхисий ечим қабул қилиш жараѐнларида кўп учрайдиган неврологик касалликларга тегишли бўлган бош оғриғи касалликларида синфлаштириш масаласига тадқиқ этилди.Дастурнинг биринчи босқичида информатив белгилар фазоси шакллантирилиб, иккинчи босқичида эса синфлаштириш масаласи ечилади. Бош оғриғи касалликларида бир синфга тегишли бўлган ташхислар мажмуасидан танланган ташхисни бошқаларига нисбатан муҳимлик даражасини берадиган информатив белгилар фазоси шакллантирилиб, номаълум объектни қайси объектга ўхшашлигини аниқлашнинг ҳал қилувчи қоидаси таклиф этилган.
The article describes the methodology and software based on the algorithms of computational algorithms for solving the problem of classifying definitions of medical symbols. The problem of classifying patients with headaches, which is often found in neurological diseases in software diagnostics, was studied. At the first stage of the program, an informational field is formed, and at the second stage, the problem of classification is solved. For headache disorders, a class of information was developed that is specific to the diagnostic class in order to determine the significance of the chosen diagnosis and the decisive principle of determining which object is similar to the unknown.
The article describes the methodology and software based on the algorithms of computational algorithms for solving the problem of classifying definitions of medical symbols. The problem of classifying patients with headaches, which is often found in neurological diseases in software diagnostics, was studied. At the first stage of the program, an informational field is formed, and at the second stage, the problem of classification is solved. For headache disorders, a class of information was developed that is specific to the diagnostic class in order to determine the significance of the chosen diagnosis and the decisive principle of determining which object is similar to the unknown.