With MELAX Technologies’ advanced product array
data challenges become biomedical, life science & healthcare solutions



Melax Technologies Inc. is an emerging AI company specializing in machine learning and natural language processing (NLP) in the biomedical domain. The Melax team has over 20 years of experience in developing clinical NLP methods, tools, and applications, top-ranked in a dozen international NLP challenges in the medical domain. Many NLP-based solutions such as computer-assisted medical coding, clinical decision support, surveillance, care quality, and patient safety reporting were implemented and tested in leading hospitals and high-tech companies in US and other countries.

Melax’s featured product, the CLAMP toolkit for clinical NLP, was built on top of award-winning NLP methodologies proven in many international NLP challenges. It enables recognition and automatic encoding of clinical information in narrative patient reports. Currently, CLAMP has been widely used by thousands of users from hundreds of organizations including large medical centers and leading HIT companies.

Client Commentary…

visualdx Commentary

We needed NLP functionality at our company and did not have the in-house expertise to accomplish it. We chose Melax Technologies CLAMP system to jumpstart our efforts. Ours was not a typical medical NLP application and the Melax team provided terrific support in getting us going and customizing the NLP pipeline to meet our needs. They also provided a framework for deploying the pipeline as a web service. I have always found them responsive and great to work with. We really appreciate their expertise and their can-do attitude which have allowed us to succeed in incorporating NLP into our product.”

Roy Robinson, Vice President, Technology and Medical Informatics, VisualDx

M E L A X   N L P   F E A T U R E S

M E L A X  N L P  F E A T U R E S

From clutter of text pile to structured, organized and standardized data
High-performance NLP components built for clinical text:
  • Built on proven methods and models trained using clinical corpora.
  • Winning algorithms from many clinical NLP challenges such as i2b2 clinical NER (2009/2010-#2), SHARE/CLEF (2013-#1), and SemEval2014 UMLS encoding (#1).
Machine learning and hybrid approaches
  • Train your own models using machine learning and deep learning algorithms with a simple click
  • Compare different models with provided evaluation programs and visualization interfaces
Annotation and corpora management
  • Built-in annotation tool that supports different IO methods (e.g. files or databases) and collaborative annotation by a team
  • Compatible/convertible between different annotation tools (e.g., Brat, eHost, MAE etc.)
Customized pipelines
  • Build your own NLP pipelines using both machine learning and rules
  • Leverage existing pipelines to avoid NLP development from scratch
Knowledge bases and sample clinical text:
  • Provide all the knowledge bases (e.g., dictionaries) required for CLAMP components
  • Come with over 300 simulated clinical notes annotated with entities and relations
Interoperability and Scalability
  • Build on the UIMA framework, thus compatible with other systems such as cTAKES
  • Thread safe and validated on parallel computing platforms such as SPARK and Hadoop

U S E    C A S E S

Make your EHR alive
Healthcare outcome and quality measurement

Healthcare outcome and quality measurement

Reports of problem-specific clinical measures
Extraction of patient safety indicators
Normalization to standard terminologies such as SNOMED-CT and MedDRA
Predictive modeling and precision medicine

Predictive modeling and precision medicine

Hospital length-of-stay and re-admission prediction
CDSS for personalized treatment
Precision oncology
Biomedical Research

Biomedical Research

Phenotyping/cohort identification
Comparative effectiveness research
ETL to common data model (CDM)
Computer assisted coding

Computer assisted coding

Medical Billing Codes: ICD 10, HCC, CPT etc.
Morphology and topology standardization for tumor registries
Patient risk assessment for CMS reimbursement
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