Use Cases


Learn more about how we implement our technologies into real-world applications.

CLAMP for Hospitals and Clinics:

Computer-Assisted Coding(CAC):

Melax has worked with multiple clients to develop CLAMP-based CAC systems for both ICD-10 and Hierarchical Chronic Conditions(HCC) codes to improve reimbursement rate and reduce the manual coding workload. Such a CAC system typically consists of NLP components such as name entities recognition, relation extraction, concept normalization and utilizing both machine learning and rule-based technologies.



Healthcare Quality Reporting:

Quality measures help quantify healthcare processes, outcomes, and organizational structure and systems. Melax has developed NLP-based approaches for quality measurement reporting. For example, we developed a system for extracting Venous thromboembolism (VTE) mentions from radiology reports and encoding them to SNOMED concepts, for one of the meaningful use criteria. Leveraging the award-winning algorithms implemented in CLAMP, an extremely high sensitivity of 0.98 and a reasonable PPV of 90% for the detection of VTE cases was achieved at a client site.


CLAMP for Health Insurance:

Automate insurance claims:

To facilitate automation of the insurance claims process by predicting diagnosis from clinical notes written by providers using CLAMP Melax developed a suctomized NLP solution for extraction and normalization diagnoses mentions into SNOMED concepts. The developed solution was deployed on a public cloud service, and further integrated into the client’s Software as a service (SaaS) platform.


CLAMP for Pharmaceutical Industry:

Systematic review of literature:

Discovery of biomedical knowledge from a massive scientific literature is an arduous task. By leveraging the award-winning biomedical NLP engine developed at Melax, scientists and researchers now can be relieved of expensive and time-consuming literature search/review, and truly focus on their innovation in research and development. For example, we are offering a systematic review tool that implements an online learning algorithm to automatically learn and classify relevant document during the review process.



Parsing eligibility criteria of clinical trials:

Personalized cancer therapy, which provides tailored treatments based on a patient’s specific characteristics (e.g. genetic status), has shown great promise for improving outcomes for cancer patients. Meanwhile, hundreds of clinical trials are investigating drugs that target specific genetic alterations in tumors. A CLAMP based system was developed by Melax for extracting genetic alteration information for personalized cancer therapy form ClinicalTrials.gov.