Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study

Computer Science

• Case Study 100%
• Natural Language Processing 100%
• Explainable Artificial Intelligence 100%
• Long Short-Term Memory Neural Network 100%
• Multiclass Classification 66%
• Neural Network Architecture 66%
• Bidirectional Encoder Representations From Transformers 66%
• Performance Measure 33%
• Classification Performance 33%
• Classification Models 33%
• Unstructured Data 33%
• Detection Performance 33%
• Preprocessing Technique 33%
• Preventive Measure 33%
• Risk Individual 33%
• Machine Learning 33%
• Learning System 33%
• Feature Extraction 33%
• Model Architecture 33%
• Word2vec 33%
• Binary Classification 33%

Biochemistry, Genetics and Molecular Biology

• Electronic Health Record 100%
• Artificial Intelligence 100%
• Smoking Habit 75%
• Short Term Memory 75%
• Natural Language Processing 75%
• Feature Extraction 25%