Basic Processing Models of Artificial Intelligence In Clinical Microbiology Laboratories

Year 2019, Volume: 3 Issue: 2, 66 - 71, 29.08.2019

Ahmet Rıza Şahin , Selma Ateş Mücahid Günay

https://doi.org/10.34084/bshr.602790

Cited By: 1

Abstract

Although the main interest of artificial intelligence in medicine seems to be to develop methods that can offer diagnostic and therapeutic recommendations, it includes numerous areas such
as physician and nurse clinical decision support systems, pharmacy decision support systems, patient care, clinical data pooling, data sharing between units and institutions, storage, interp-
retation, business intelligence and machine learning. In addition to having a strong orientation towards automation, expert systems and artificial intelligence, medical laboratories have an
increasing need especially for expert systems. Clinical microbiology laboratories are a central element in the identification of data chains that may be involved in the fight against antimicrobial
resistance. By the integration of artificial intelligence to clinical microbiology laboratory use, it is aimed to provide detailed support to individual epidemiological surveillance, research appli-
cations and to improve individual patient care quality. In our study, the principles and methods of the study of artificial intelligence in clinical microbiology and antibiotic resistance processing
were reviewed and important clinical studies were examined. 

Keywords

Microbiology, Artificial intelligence, Antibiotic resistance

Klinik Mikrobiyoloji Laboratuvarlarında Yapay Zekanın Temel İşleyiş Modelleri

Abstract

Yapay
zekanın tıp alanındaki ana ilgi alanı, teşhis ve tedavi önerileri sunabilecek
yöntemler geliştirmek gibi görünse de hekim ve hemşire klinik karar destek sistemleri, eczane karar destek
sistemleri, hasta bakımı, klinik veri havuzu oluşturulması, birimler ve
kurumlar arası veri paylaşımı, depolama, yorumlayabilmeye sürecine katkı ile
beraber olarak iş zekası ve makine öğrenmesi gibi sayısız alanı kapsar. Tıbbi laboratuvarlar
otomasyon, uzman sistemler ve yapay zekaya doğru güçlü bir yönelimle karşı karşıya
olmanın yanısıra uzman sistemlere yönelik artan bir ihtiyaç yaşamaktadır. Klinik
mikrobiyoloji laboratuvarları antimikrobiyal dirence karşı mücadelede yer
alabilecek veri zincirlerinin tespitinde merkezi bir unsurdur. Yapay zekanın klinik mikrobiyoloji laboratuvar kullanımına entegrasyonun
amaçları arasında bireysel epidemiyolojik sürveyans, araştırma uygulamalarına
ayrıntılı destek sağlamanın yanı sıra bireysel hasta bakım kalitesini artırmak
yer alır. Çalışmamızda klinik mikrobiyoloji ve antibiyotik
direncinin işlenmesi konusunda farklı
yapay zeka çalışma prensip ve yöntemleri gözden geçirilerek, bu yöntemleri
irdeleyen önemli klinik çalışmalar incelenmiştir.

Keywords

Yapay zeka, Mikrobiyoloji, Antibiyotik direnci

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