| pubmed-article:9891147 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C0006142 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C2926606 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C0242406 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C2607943 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C0679831 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C1280500 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C1511726 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C0681842 | lld:lifeskim |
| pubmed-article:9891147 | lifeskim:mentions | umls-concept:C2004457 | lld:lifeskim |
| pubmed-article:9891147 | pubmed:issue | 1 | lld:pubmed |
| pubmed-article:9891147 | pubmed:dateCreated | 1999-3-23 | lld:pubmed |
| pubmed-article:9891147 | pubmed:abstractText | The authors evaluated the contribution of medical history data to the prediction of breast cancer with artificial neural network (ANN) models based on mammographic findings. | lld:pubmed |
| pubmed-article:9891147 | pubmed:language | eng | lld:pubmed |
| pubmed-article:9891147 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:9891147 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:9891147 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:9891147 | pubmed:month | Jan | lld:pubmed |
| pubmed-article:9891147 | pubmed:issn | 1076-6332 | lld:pubmed |
| pubmed-article:9891147 | pubmed:author | pubmed-author:BakerJ AJA | lld:pubmed |
| pubmed-article:9891147 | pubmed:author | pubmed-author:RoJ SJS | lld:pubmed |
| pubmed-article:9891147 | pubmed:author | pubmed-author:FloydC ECEJr | lld:pubmed |
| pubmed-article:9891147 | pubmed:author | pubmed-author:KornguthP JPJ | lld:pubmed |
| pubmed-article:9891147 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:9891147 | pubmed:volume | 6 | lld:pubmed |
| pubmed-article:9891147 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:9891147 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:9891147 | pubmed:pagination | 10-5 | lld:pubmed |
| pubmed-article:9891147 | pubmed:dateRevised | 2006-11-15 | lld:pubmed |
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| pubmed-article:9891147 | pubmed:year | 1999 | lld:pubmed |
| pubmed-article:9891147 | pubmed:articleTitle | Effect of patient history data on the prediction of breast cancer from mammographic findings with artificial neural networks. | lld:pubmed |
| pubmed-article:9891147 | pubmed:affiliation | Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA. | lld:pubmed |
| pubmed-article:9891147 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:9891147 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |
| pubmed-article:9891147 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:9891147 | lld:pubmed |
