Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...

BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...

Organizing data labeling for machine learning is not a one sitting job, yet a single error by a data labeler may cost you a fortune. Now, you probably wonder how do I ...

Ease of use, more big data than ever, and a proliferation of libraries and toolkits helped machine learning leap ahead for many Until recently, machine learning was an esoteric discipline, used only ...