id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-279125-w6sh7xpn	Egli, Adrian	Digital microbiology	2020-06-27		.txt	text/plain	1602	110	41	Making an efficient use of big data, machine learning, and artificial intelligence in clinical microbiology requires a profound understanding of data handling aspects. clinical decision support systems based on machine learning to provide automated feedback 7 regarding empiric antibiotic prescription adapted to specific patient groups 46 . As physiology and laboratory parameters can rapidly change 9 during an infection, time-series data greatly impact the predictive values of such algorithms -similar 10 to a doctor, who observers the patient during disease progression -machine learning algorithms will 11 also follow the patient's data stream. Machine 18 learning algorithms may be used at each step of the microbiological diagnostic process from pre-to 19 post-analytics, helping us to deal with the increasing quantities and complexity of data 113,114 (Table 1) . Machine learning radically changes the way we 8 handle healthcare-related data -including data of clinical microbiology and infectious diseases.	./cache/cord-279125-w6sh7xpn.txt	./txt/cord-279125-w6sh7xpn.txt