Biosurveillance for invasive fungal infections via text mining

Keyphrases

• Biosurveillance 100%
• Text Mining 100%
• Invasive Fungal Disease 100%
• Invasive Fungal Infection 100%
• Melbourne 18%
• Language Technology 18%
• Aspergillosis 18%
• Australia 9%
• Life-threatening 9%
• Systems-based 9%
• Text-dependent 9%
• Machine Learning 9%
• Medical Experts 9%
• Health Systems 9%
• Computed Tomography 9%
• Patient Time 9%
• Mortality Rate 9%
• Processing Technology 9%
• Cancer Center 9%
• Machine Learning Approach 9%
• Automatically Identify 9%
• Bag of Visual Words (BoVW) 9%
• Patient-level 9%
• Annotator 9%
• Radiology Reports 9%
• Multi-keyword 9%
• Cause of Disease 9%
• Punctuation 9%
• In-hospital Death 9%
• Language Processing 9%
• MetaMap 9%
• Hospital-acquired Infection 9%
• Text Mining Techniques 9%
• Classification Level 9%
• Concept Description 9%
• Multiple Scans 9%
• Aspergillus 9%
• Log-likelihood Ratio 9%
• Statistical Machine Learning 9%
• Common Life 9%
• Concept Base 9%
• Diagnosis Stage 9%
• Weka 9%

Medicine and Dentistry

• Fungal Infection 100%
• Systemic Mycosis 100%
• Biosurveillance 100%
• Diseases 18%
• Aspergillosis 18%
• Health Care Cost 9%
• Malignant Neoplasm 9%
• Infection 9%
• Health System 9%
• Mortality Rate 9%
• Radiology 9%
• Language Processing 9%
• Hospital Infection 9%
• Aspergillus 9%
• X-Ray Computed Tomography 9%

Computer Science

• Text Mining 100%
• Machine Learning 33%
• Learning System 33%
• Likelihood Ratio 33%
• Support Vector Machine 33%
• Collected Data 33%
• Machine Learning Approach 33%
• Language Processing 33%
• Mining Technique 33%
• Concept Description 33%