Using Machine Learning Algorithms to Identify Key Predictors of Invasive Mold Infection Surveillance.
Saved in:
| Title: | Using Machine Learning Algorithms to Identify Key Predictors of Invasive Mold Infection Surveillance. |
|---|---|
| Authors: | Williams SL; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Salah Z; Surveillance, Information Management, and Statistics Office, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Jackson BR; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Wurster S; Division of Internal Medicine, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA., Serpa JA; Section of Infectious Diseases, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA., Grimes CZ; Division of Infectious Diseases, McGovern Medical School, University of Texas, Houston, Texas, USA., Atmar RL; Section of Infectious Diseases, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA., Chiller TM; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Kontoyiannis DP; Division of Internal Medicine, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA., Ostrosky-Zeichner L; Division of Infectious Diseases, McGovern Medical School, University of Texas, Houston, Texas, USA., Toda M; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. |
| Source: | The Journal of infectious diseases [J Infect Dis] 2025 Dec 20; Vol. 232 (6), pp. e1033-e1042. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: United States NLM ID: 0413675 Publication Model: Print Cited Medium: Internet ISSN: 1537-6613 (Electronic) Linking ISSN: 00221899 NLM ISO Abbreviation: J Infect Dis Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40458914 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Using Machine Learning Algorithms to Identify Key Predictors of Invasive Mold Infection Surveillance. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Williams+SL%22">Williams SL</searchLink>; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Salah+Z%22">Salah Z</searchLink>; Surveillance, Information Management, and Statistics Office, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Jackson+BR%22">Jackson BR</searchLink>; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Wurster+S%22">Wurster S</searchLink>; Division of Internal Medicine, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Serpa+JA%22">Serpa JA</searchLink>; Section of Infectious Diseases, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Grimes+CZ%22">Grimes CZ</searchLink>; Division of Infectious Diseases, McGovern Medical School, University of Texas, Houston, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Atmar+RL%22">Atmar RL</searchLink>; Section of Infectious Diseases, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Chiller+TM%22">Chiller TM</searchLink>; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Kontoyiannis+DP%22">Kontoyiannis DP</searchLink>; Division of Internal Medicine, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Ostrosky-Zeichner+L%22">Ostrosky-Zeichner L</searchLink>; Division of Infectious Diseases, McGovern Medical School, University of Texas, Houston, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Toda+M%22">Toda M</searchLink>; Mycotic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%220413675%22">The Journal of infectious diseases</searchLink> [J Infect Dis] 2025 Dec 20; Vol. 232 (6), pp. e1033-e1042. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Oxford+University+Press%22">Oxford University Press </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>0413675 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1537-6613 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200221899%22">00221899 </searchLink><i>NLM ISO Abbreviation: </i>J Infect Dis <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40458914 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/infdis/jiaf219 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: e1033 Titles: – TitleFull: Using Machine Learning Algorithms to Identify Key Predictors of Invasive Mold Infection Surveillance. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Williams SL – PersonEntity: Name: NameFull: Salah Z – PersonEntity: Name: NameFull: Jackson BR – PersonEntity: Name: NameFull: Wurster S – PersonEntity: Name: NameFull: Serpa JA – PersonEntity: Name: NameFull: Grimes CZ – PersonEntity: Name: NameFull: Atmar RL – PersonEntity: Name: NameFull: Chiller TM – PersonEntity: Name: NameFull: Kontoyiannis DP – PersonEntity: Name: NameFull: Ostrosky-Zeichner L – PersonEntity: Name: NameFull: Toda M IsPartOfRelationships: – BibEntity: Dates: – D: 20 M: 12 Text: 2025 Dec 20 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 1537-6613 Numbering: – Type: volume Value: 232 – Type: issue Value: 6 Titles: – TitleFull: The Journal of infectious diseases Type: main |
| ResultId | 1 |