Machine learning for tackling microbiota data and infection complications in immunocompromised patients with cancer

Journal of Internal Medicine

Volumn 284, Issue 2, 2018, Pages 189-192

  Espinoza, J Luis ^a  

^a KINKI UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIBIOTIC AGENT; BIOLOGICAL MARKER; RNA 16S;

ANTIMICROBIAL THERAPY; ARTIFICIAL INTELLIGENCE; BACTERIAL GENOME; BLOODSTREAM INFECTION; CANCER CHEMOTHERAPY; CANCER PATIENT; CANCER SURVIVAL; CANDIDA ALBICANS; CLINICAL OUTCOME; EXTENDED SPECTRUM BETA LACTAMASE PRODUCING ESCHERICHIA COLI; FEVER; HEALTH CARE QUALITY; HEMATOLOGIC MALIGNANCY; HEMATOPOIETIC STEM CELL TRANSPLANTATION; HUMAN; IMMUNOCOMPROMISED PATIENT; INFECTION COMPLICATION; INFECTION RISK; INTENSIVE CARE; INTESTINE FLORA; LENGTH OF STAY; MACHINE LEARNING; METABOLOMICS; MICROBIAL COMMUNITY; MORBIDITY; MORTALITY; NEUTROPENIA; NOTE; OVERALL SURVIVAL; PEPTOCLOSTRIDIUM DIFFICILE; PERITONITIS; PRIORITY JOURNAL; PSEUDOMONAS AERUGINOSA; SEPSIS; THORAX RADIOGRAPHY; VANCOMYCIN RESISTANT ENTEROCOCCUS;

EID: 85044244357     PISSN: 09546820     EISSN: 13652796     Source Type: Journal    
DOI: 10.1111/joim.12746     Document Type: Note

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