Identification of antibiotic resistance profiles in diabetic foot infections: A machine learning proof-of-concept analysis.
| Publicado en: | International Journal of Diabetes in Developing Countries Vol. 46; no. 1; pp. 193 - 201 |
|---|---|
| Autores principales: | , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Mar2026
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192344065&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192344065 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09733930 259E jtl: International Journal of Diabetes in Developing Countries issn: 09733930 maglogo: N pubinfo: dt: Mar2026 vid: 46 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 192344065 184379635 192344065 192344065 10.1007/s13410-025-01490-1 192344065 ppf: 193 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Identification of antibiotic resistance profiles in diabetic foot infections: A machine learning proof-of-concept analysis. aug: au: Carrillo-Larco, Rodrigo M. de Elvira Mori Orrillo, Edmundo Castillo-Cara, Manuel García, Raúl Yovera-Aldana, Marlon Bernabe-Ortiz, Antonio affil: https://ror.org/03czfpz43 Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA sug: subj: Drug Resistance, Microbial Diabetic Foot Microbiology Diabetic Foot Diagnosis Diabetes Mellitus Complications Machine Learning Utilization Gram-Positive Bacteria Gram-Negative Bacteria Bacterial Infections Classification Human Funding Source Peru Male Female Hospitals Retrospective Design Secondary Analysis Prospective Studies Pilot Studies Adult Middle Age Aged Diagnosis, Laboratory Logistic Regression Confidence Intervals Descriptive Statistics Data Analysis Software Analysis of Variance Chi Square Test Decision Trees Predictive Value of Tests Models, Statistical Blood Glucose Leukocyte Count Hemoglobins Kidney Function Tests Random Forest Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Male Female pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|