A data mining approach to investigate food groups related to incidence of bladder cancer in the BLadder cancer Epidemiology and Nutritional Determinants International Study.

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Fältnamn	Indikatorer	Metadata
000		04334naa a2200721 4500
001		oai:DiVA.org:uu-427569
003		SwePub
008		201209s2020 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
009		oai:prod.swepub.kib.ki.se:144424151
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4275692 URI
024	7	a https://doi.org/10.1017/S00071145200014392 DOI
024	7	a http://kipublications.ki.se/Default.aspx?queryparsed=id:1444241512 URI
040		a (SwePub)uud (SwePub)ki
041		a engb eng
042		9 SwePub
072	7	a ref2 swepub-contenttype
072	7	a art2 swepub-publicationtype
100	1	a Yu, Evan Y W4 aut
245	1 0	a A data mining approach to investigate food groups related to incidence of bladder cancer in the BLadder cancer Epidemiology and Nutritional Determinants International Study.
264	1	b Cambridge University Press,c 2020
338		a print2 rdacarrier
520		a At present, analysis of diet and bladder cancer (BC) is mostly based on the intake of individual foods. The examination of food combinations provides a scope to deal with the complexity and unpredictability of the diet and aims to overcome the limitations of the study of nutrients and foods in isolation. This article aims to demonstrate the usability of supervised data mining methods to extract the food groups related to BC. In order to derive key food groups associated with BC risk, we applied the data mining technique C5.0 with 10-fold cross-validation in the BLadder cancer Epidemiology and Nutritional Determinants study, including data from eighteen case-control and one nested case-cohort study, compromising 8320 BC cases out of 31 551 participants. Dietary data, on the eleven main food groups of the Eurocode 2 Core classification codebook, and relevant non-diet data (i.e. sex, age and smoking status) were available. Primarily, five key food groups were extracted; in order of importance, beverages (non-milk); grains and grain products; vegetables and vegetable products; fats, oils and their products; meats and meat products were associated with BC risk. Since these food groups are corresponded with previously proposed BC-related dietary factors, data mining seems to be a promising technique in the field of nutritional epidemiology and deserves further examination.
650	7	a MEDICIN OCH HÄLSOVETENSKAPx Hälsovetenskapx Näringslära0 (SwePub)303042 hsv//swe
650	7	a MEDICAL AND HEALTH SCIENCESx Health Sciencesx Nutrition and Dietetics0 (SwePub)303042 hsv//eng
650	7	a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Cancer och onkologi0 (SwePub)302032 hsv//swe
650	7	a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Cancer and Oncology0 (SwePub)302032 hsv//eng
653		a Bladder cancer
653		a Data mining
653		a Epidemiological studies
653		a Food groups
700	1	a Wesselius, Anke4 aut
700	1	a Sinhart, Christoph4 aut
700	1	a Wolk, Alicjau Karolinska Institutet4 aut0 (Swepub:uu)alwol516
700	1	a Stern, Mariana Carla4 aut
700	1	a Jiang, Xuejuan4 aut
700	1	a Tang, Li4 aut
700	1	a Marshall, James4 aut
700	1	a Kellen, Eliane4 aut
700	1	a van den Brandt, Piet4 aut
700	1	a Lu, Chih-Ming4 aut
700	1	a Pohlabeln, Hermann4 aut
700	1	a Steineck, Gunnar4 aut
700	1	a Allam, Mohamed Farouk4 aut
700	1	a Karagas, Margaret R4 aut
700	1	a La Vecchia, Carlo4 aut
700	1	a Porru, Stefano4 aut
700	1	a Carta, Angela4 aut
700	1	a Golka, Klaus4 aut
700	1	a Johnson, Kenneth C4 aut
700	1	a Benhamou, Simone4 aut
700	1	a Zhang, Zuo-Feng4 aut
700	1	a Bosetti, Cristina4 aut
700	1	a Taylor, Jack A4 aut
700	1	a Weiderpass, Elisabete4 aut
700	1	a Grant, Eric J4 aut
700	1	a White, Emily4 aut
700	1	a Polesel, Jerry4 aut
700	1	a Zeegers, Maurice P A4 aut
710	2	a Karolinska Institutet4 org
773	0	t British Journal of Nutritiond : Cambridge University Pressg 124:6, s. 611-619q 124:6<611-619x 0007-1145x 1475-2662
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-427569
856	4 8	u https://doi.org/10.1017/S0007114520001439
856	4 8	u http://kipublications.ki.se/Default.aspx?queryparsed=id:144424151

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