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The recent Transformer-based pre-trained language models (e.g., BERT, Bi-directional Encoding Representations from Transformers 54 ) usually require a limited length of up to 512 sub-word tokens (where a word can be tokenised into several sub-words) as input due to the memory-demanding self-attention mechanism, while discharge summaries alone in MIMIC-III have on average around 1500 tokens or words 19 and up to over 10,000 tokens, not counting other types of clinical notes

Starting with well-tolerated compounds allows you to assess individual responses and build experience before progressing to more complex protocols

Postgrad Med J 79: 218-220

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