[ CourseWikia.com ] Advanced AI - NLP Techniques for Clinical Datasets
File List
- ~Get Your Files Here !/04 - 3. Clinical Text Representation/02 - Clinical text representation using fastText.mp4 24.2 MB
- ~Get Your Files Here !/02 - 1. Clinical Named Entity Recognition (CNER)/02 - Clinical named entity recognition using scispaCy.mp4 19.4 MB
- ~Get Your Files Here !/03 - 2. Clinical Entity Resolution/03 - Entity linkage and resolution with a biomedical knowledge base.mp4 16.9 MB
- ~Get Your Files Here !/03 - 2. Clinical Entity Resolution/02 - Medical abbreviation resolution with scispaCy.mp4 11.1 MB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/04 - Clinical word prediction using transformers.mp4 9.6 MB
- ~Get Your Files Here !/04 - 3. Clinical Text Representation/03 - Clinical text representation using Universal Sentence Encoder (USE).mp4 9.0 MB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/02 - Clinical diagnosis prediction using transformers.mp4 8.2 MB
- ~Get Your Files Here !/02 - 1. Clinical Named Entity Recognition (CNER)/01 - What is clinical named entity recognition (CNER).mp4 7.8 MB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/03 - Clinical named entity recognition using transformers.mp4 7.0 MB
- ~Get Your Files Here !/03 - 2. Clinical Entity Resolution/01 - What is clinical entity resolution.mp4 6.0 MB
- ~Get Your Files Here !/04 - 3. Clinical Text Representation/01 - What is clinical text representation.mp4 4.7 MB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/01 - What are transformers.mp4 4.7 MB
- ~Get Your Files Here !/01 - Introduction/03 - How to use the exercise files.mp4 3.9 MB
- ~Get Your Files Here !/01 - Introduction/01 - Use NLP techniques for your data.mp4 3.6 MB
- ~Get Your Files Here !/06 - Conclusion/01 - Next steps.mp4 1005.8 KB
- ~Get Your Files Here !/01 - Introduction/02 - What you should know.mp4 481.2 KB
- ~Get Your Files Here !/04 - 3. Clinical Text Representation/02 - Clinical text representation using fastText.srt 8.5 KB
- ~Get Your Files Here !/02 - 1. Clinical Named Entity Recognition (CNER)/02 - Clinical named entity recognition using scispaCy.srt 6.2 KB
- ~Get Your Files Here !/02 - 1. Clinical Named Entity Recognition (CNER)/01 - What is clinical named entity recognition (CNER).srt 5.9 KB
- ~Get Your Files Here !/03 - 2. Clinical Entity Resolution/03 - Entity linkage and resolution with a biomedical knowledge base.srt 5.8 KB
- ~Get Your Files Here !/03 - 2. Clinical Entity Resolution/01 - What is clinical entity resolution.srt 5.1 KB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/02 - Clinical diagnosis prediction using transformers.srt 3.7 KB
- ~Get Your Files Here !/04 - 3. Clinical Text Representation/01 - What is clinical text representation.srt 3.6 KB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/04 - Clinical word prediction using transformers.srt 3.3 KB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/01 - What are transformers.srt 3.1 KB
- ~Get Your Files Here !/03 - 2. Clinical Entity Resolution/02 - Medical abbreviation resolution with scispaCy.srt 3.1 KB
- ~Get Your Files Here !/04 - 3. Clinical Text Representation/03 - Clinical text representation using Universal Sentence Encoder (USE).srt 2.8 KB
- ~Get Your Files Here !/05 - 4. Transformers for Clinical Text/03 - Clinical named entity recognition using transformers.srt 2.7 KB
- ~Get Your Files Here !/01 - Introduction/03 - How to use the exercise files.srt 1.5 KB
- ~Get Your Files Here !/01 - Introduction/01 - Use NLP techniques for your data.srt 1.2 KB
- ~Get Your Files Here !/06 - Conclusion/01 - Next steps.srt 769 bytes
- ~Get Your Files Here !/Ex_Files_Advanced_AI_NLP_Techniques_Clinical_Datasets.zip 445 bytes
- ~Get Your Files Here !/01 - Introduction/02 - What you should know.srt 425 bytes
- ~Get Your Files Here !/Bonus Resources.txt 386 bytes
- Get Bonus Downloads Here.url 181 bytes
Download Torrent
Related Resources
Copyright Infringement
If the content above is not authorized, please contact us via anywarmservice[AT]gmail.com. Remember to include the full url in your complaint.