MARC details
| 000 -LEADER |
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| fixed length control field |
02231nam a22003737a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
171205s20172017 xxu||||| |||| 00| 0 eng d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
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| International Standard Serial Number |
2045-2322 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
Ovid MEDLINE(R) |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
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| PMID |
29138438 |
| 245 ## - TITLE STATEMENT |
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| Title |
Network-based analysis of diagnosis progression patterns using claims data. |
| 251 ## - Source |
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| Source |
Scientific Reports. 7(1):15561, 2017 Nov 14 |
| 252 ## - Abbreviated Source |
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| Abbreviated source |
Sci. rep.. 7(1):15561, 2017 Nov 14 |
| 253 ## - Journal Name |
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| Journal name |
Scientific reports |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Year |
2017 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Manufacturer |
FY2018 |
| 266 ## - Date added to catalog |
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| Date added to catalog |
2017-12-05 |
| 520 ## - SUMMARY, ETC. |
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| Abstract |
In recent years, several network models have been introduced to elucidate the relationships between diseases. However, important risk factors that contribute to many human diseases, such as age, gender and prior diagnoses, have not been considered in most networks. Here, we construct a diagnosis progression network of human diseases using large-scale claims data and analyze the associations between diagnoses. Our network is a scale-free network, which means that a small number of diagnoses share a large number of links, while most diagnoses show limited associations. Moreover, we provide strong evidence that gender, age and disease class are major factors in determining the structure of the disease network. Practically, our network represents a methodology not only for identifying new connectivity that is not found in genome-based disease networks but also for estimating directionality, strength, and progression time to transition between diseases considering gender, age and incidence. Thus, our network provides a guide for investigators for future research and contributes to achieving precision medicine. |
| 546 ## - LANGUAGE NOTE |
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| Language note |
English |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
*Diagnosis |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
*Neural Networks (Computer) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
*Precision Medicine |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Age Factors |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Gender Identity |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Genome, Human |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Humans |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Risk Factors |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME |
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| Institution |
MedStar Washington Hospital Center |
| 656 ## - INDEX TERM--OCCUPATION |
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| Department |
Pathology |
| 657 ## - INDEX TERM--FUNCTION |
|---|
| Medline publication type |
Journal Article |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Local Authors |
Ko, Kyungmin |
| 790 ## - Authors |
|---|
| All authors |
Han HW, Jeong E, Ko K, Oh S |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| DOI |
<a href="https://dx.doi.org/10.1038/s41598-017-15647-4">https://dx.doi.org/10.1038/s41598-017-15647-4</a> |
| Public note |
https://dx.doi.org/10.1038/s41598-017-15647-4 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Journal Article |
| Item type description |
Article |
