John Snow Labs is emerging as the clear industry leader for state-of-the-art NLP in healthcare.
We cannot recommend a better way to apply the most current, accurate, and scalable technology to your natural language understanding challenges today.
What’s in the Box
Clinical Entity Recognition
40 units
DOSAGE
of
insulin glargine
drug
at night
FREQUENCY
Algorithms
Extract Knowledge
- Entity Linker
- Entity Disambiguator
- Document Classifier
- Contextual Parser
Split Text
- Sentence Detector
- Deep Sentence Detector
- Tokenizer
- nGram Generator
Clinical Grammar
- Stemmer
- Lemmatizer
- Part of Speech Tagger
- Dependency Parser
Clinical Entity Linking
Suspect diabetes
SNOMED-CT:
473127005
Lisinopril 10 MG
RxNorm:
316151
Hyponatremia
ICD-10:
E87.1
Algorithms
De-Identity Text
- Structured Data
- Unstructured Text
- Obfuscator
- Generalizer
Clean Medical Text
- Spell Checking
- Spell Correction
- Normalizer
- Stopword Cleaner
Find in Text
- Text Matcher
- Regex Matcher
- Date Matcher
- Chunker
Assertion Status
Fever and sore throat
PRESENT
No stomach pain
ABSENT
Father with Alzheimer
FAMILY
Content
Medical Transformers
JSL-BERT-ClinicalBioBERTClinicalBERTGloVe-MedGloVe-ICD-OBlueBert
Relation Extraction
Ora
NAME
a
25
AGE
yo
cashier
PROFESSION
from
Morocco
LOCATION
Content
Linked Medical Terminologies
SNOMED-CTCPTUMLSICD-10-CMRxNormHPOICD-10-PCSICD-OLOINC
700+ Pretrained Models
Clinical:
Signs, Symptoms, Treatments, Procedures, Tests, Labs, Sections
Anatomy:
Organ, Subdivision, Cell, Structure Organism, Tissue, Gene, Chemical
Drugs:
Name, Dosage, Strength, Route, Duration, Frequency, Poisons, Adverse Effects
Demographics:
Age, Gender, Height, Weight, Race, Ethnisity, Marital Status, Vital Signs
Risk Factors:
Smoking, Obesity, Diabetes, Hypertension, Substance Abuse
Sensitive Data:
Patient Name, Address, Phone, Email, Dates, Providers, Identifiers
Trainable & Tunable
Scalable to a Cluster
Fast Inference
Hardware Optimized
Community
Spark NLP for Healthcare in action
Clinical Entity Recognition
Clinical Entity Linking
Assertion Status
Deidentification
State Of The Art Accuracy
Production-Grade, Fast & Trainable Implementation of State-of-the-Art Biomedical NLP Research
“BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”, Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, CoRR, 2018
“Entity Recognition from Clinical Texts via Recurrent Neural Network”, Liu et al., BMC Medical Informatics & Decision Making, July 2017.
“CNN-based ranking for biomedical entity normalization”, Li et al., BMC Bioinformatics, October 2017.
“Neural Networks For Negation Scope Detection“, Fancellu et al., In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016.
“How to Train Good Word Embeddings for Biomedical NLP, Billy Chiu, Gamal Crichton“, Anna Korhonen, Sampo Pyysalo, Proceedings of the 15th Workshop on Biomedical Natural Language Processing, 2016
