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Wyświetlanie 1-3 z 3
Tytuł:
Noninvasive blood glucose level monitoring for predicting insulin infusion rate using multivariate data
Autorzy:
Geetha, G.
Ponsam, J. Godwin
Nimala, K.
Powiązania:
https://bibliotekanauki.pl/articles/38709458.pdf
Data publikacji:
2024
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
CGM
fog computing
hypoglycemia
hyperglycemia
Apriori algorithm
obliczenie mgły
hipoglikemia
hiperglikemia
Algorytm Apriori
Opis:
Diabetes stands as the most widely recognized acute disease globally, resulting in death when it is not treated in an appropriate manner and time. We have developed a closedloop control system that uses continuous glucose, carbohydrate, and physiological variable data to regulate glucose levels and treat hyperglycemia and hypoglycemia, as well as a hypoglycemia early warning module. Overall, the proposed models are effective at predicting a normal glycemic range from >70 to 180 mg/dl, hypoglycemic values of <70 mg/dl, and hyperglycemic value of 180 mg/dl blood sugar levels. We undertook a seven-day, day-and-night home study with 15 adults. Initially, we started with checking insulin levels after meal consumption, and later, we concentrated on how our system reacted to the physical activity of the patients. Evaluation was conducted based on performance parameters such as precision (0.87), recall (0.87), F-score (0.82), delay (26.5±3), and error size (1.14±2).
Źródło:
Computer Assisted Methods in Engineering and Science; 2024, 31, 2; 157-174
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of data mining techniques to find relationships between the dishes offered by a restaurant for the elaboration of combos based on the preferences of the diners
Autorzy:
Vazquez, Rosa Maria
Bonilla, Edmundo
Sanchez, Eduardo
Atriano, Oscar
Berruecos, Cinthya
Powiązania:
https://bibliotekanauki.pl/articles/118001.pdf
Data publikacji:
2019
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
data mining
association rules
apriori algorithm
combos
Web Service
eksploracja danych
reguły asocjacji
algorytm a priori
kombinacje
Opis:
Currently, blended food has been a common menu item in fast food restaurants. The sales of the fast-food industry grow thanks to several sales strategies, including the “combos”, so, specialty, regional, family and buffet restaurants are even joining combos’ promotions. This research paper presents the implementation of a system that will serve as support to elaborate combos according to the preferences of the diners using data mining techniques to find relationships between the different dishes that are offered in a restaurant. The software resulting from this research is being used by the mobile application Food Express, with which it communicates through webservices. References
Źródło:
Applied Computer Science; 2019, 15, 2; 73-88
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative evaluation of the different data mining techniques used for the medical database
Autorzy:
Kasperczuk, A.
Dardzińska, A.
Powiązania:
https://bibliotekanauki.pl/articles/386432.pdf
Data publikacji:
2016
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
data mining
classification
WEKA
J48
MLP
apriori
association rules
baza wiedzy medycznej
eksploracja danych
algorytm klasyfikacji
Opis:
Data mining is the upcoming research area to solve various problems. Classification and finding association are two main steps in the field of data mining. In this paper, we use three classification algorithms: J48 (an open source Java implementation of C4.5 algorithm), Multilayer Perceptron - MLP (a modification of the standard linear perceptron) and Naïve Bayes (based on Bayes rule and a set of conditional independence assumptions) of the Weka interface. These classifiers have been used to choose the best algorithm based on the conditions of the voice disorders database. To find association rules over transactional medical database first we use apriori algorithm for frequent item set mining. These two initial steps of analysis will help to create the medical knowledgebase. The ultimate goal is to build a model, which can improve the way to read and interpret the existing data in medical database and future data as well.
Źródło:
Acta Mechanica et Automatica; 2016, 10, 3; 233-238
1898-4088
2300-5319
Pojawia się w:
Acta Mechanica et Automatica
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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