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OpenSource Resources

UMLS APIs for clinical vocabularies

Originally published by Bell Eapen at nuchange.ca on August 20, 2019. If you have some feedback, reach out to the author on Twitter,  LinkedIn or  Github.

UMLS, or Unified Medical Language System, is a set of files and software that brings together many health and biomedical vocabularies and standards to enable interoperability between computer systems.

Natural Language Processing (NLP) on the vast amount of data captured by electronic medical records (EMR) is gaining popularity. The recent advances in machine learning (ML) algorithms and the democratization of high-performance computing (HPC) have reduced the technical challenges in NLP. However, the real challenge is not the technology or the infrastructure, but the lack of interoperability — in this case, the inconsistent use of terminology systems.


natural language processing
UMLS for NLP

NLP tasks start with recognizing medical terms in the corpus of text and converting it into a standard terminology space such as SNOMED and ICD. This requires a terminology mapping service that can do this mapping in an easy and consistent manner. The Unified Medical Language System (UMLS) terminology server is the most popular for integrating and distributing key terminology, classification and coding standards. The consistent use of  UMLS resources leads to effective and interoperable biomedical information systems and services, including EMRs.


To make things easier, UMLS provides both REST-based and SOAP-based services that can be integrated into software applications. A high-level library that encapsulated these services, making the REST calls easy to the user is required for the efficient use of these resources.  Umlsjs is one such high-level library for the UMLS REST web services for javascript. It is free, open-source and available on NPM, making it easy to integrate into any javascript (for browsers) or any nodejs applications.


The umlsjs package is available on GitHub and the NPM. It is still work in progress and any coding/documentation contributions are welcome. Please read the CONTRIBUTING.md file on the repository for instructions. If you use it and find any issues, please report it on GitHub.


Categories
Research Resources

McMaster develops tool for COVID-19 battle

This article was first published on Brighter World. Read the original article.

McMaster University researchers have developed a tool to share with the international health sciences community which can help determine how the coronavirus that causes COVID-19 is spreading and whether it is evolving.

Simply put, the tool is a set of molecular ‘fishing hooks’ to isolate the virus, SARS-CoV-2, from biological samples. This allows laboratory researchers to gain insight into the properties of the isolated virus COVID-19 by then using a technology called next-generation sequencing.

The details were published on Preprints.org.

“You wouldn’t use this technology to diagnose the patient, but you could use it to track how the virus evolves over time, how it transmits between people, how well it survives outside the body, and to find answers to other questions,” said principal investigator Andrew McArthur, associate professor of biochemistry and biomedical sciences, and a member of the Michael G. DeGroote Institute for Infectious Disease Research (IIDR) at McMaster.

“Our tool, partnered with next-generation sequencing, can help scientists understand, for example, if the virus has evolved between patient A and patient B.”

McArthur points out that the standard technique to isolate the virus involves culturing it in cells in contained labs by trained specialists. The McMaster tool gives a faster, safer, easier and less-expensive alternative, he said.

“Not every municipality or country will have specialized labs and researchers, not to mention that culturing a virus is dangerous,” he said.

“This tool removes some of these barriers and allows for more widespread testing and analyses.”

First author Jalees Nasir, a PhD candidate in biochemistry and biomedical sciences at McMaster, has been working with McMaster and Sunnybrook Health Sciences Centre researchers to develop a bait capture tool that can specifically isolate respiratory viruses. When news recently broke of COVID-19, Nasir knew he could develop a “sequence recipe” to help researchers to isolate the novel virus more easily.

“When you have samples from a patient, for example, it can consist of a combination of virus, bacteria and human material, but you’re really only interested in the virus,” Nasir said. “It’s almost like a fishing expedition. We are designing baits that we can throw into the sample as hooks and pull out the virus from that mixture.”

The decision was made to release the sequences publicly without the normal practice of peer-review or clinical evaluation to ensure this tool was available to all quickly, recognizing the urgency of the situation, said McArthur.

The research team plans to collaborate with Sunnybrook for further testing but also hopes other scientists can quickly perform their own validation.

McArthur added that a postdoctoral fellow in his lab, David Speicher, is currently communicating details of the technology to the international clinical epidemiology community.

“Since we’re dealing with an outbreak, there was no value in us doing a traditional academic study and the experiments,” said McArthur. “We designed this tool and are releasing it for use by others.

“In part, we’re relying on our track record of knowing what we are doing, but we’re also relying on people who have the virus samples in hand being able to do the validation experiment so that it’s reliable.”

The research was funded by the Comprehensive Antibiotic Resistance Database at McMaster.

This article was first published on Brighter World. Read the original article.

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OpenSource Resources

Hephestus: Health data warehousing tool for public health and clinical research

Originally published by Bell Eapen at nuchange.ca on November 3, 2018. If you have some feedback, reach out to the author on TwitterLinkedIn or Github.

Health data warehousing is becoming an important requirement for deriving knowledge from the vast amount of health data that healthcare organizations collect. A data warehouse is vital for collaborative and predictive analytics. The first step in designing a data warehouse is to decide on a suitable data model. This is followed by the extract-transform-load (ETL) process that converts source data to the new data model amenable for analytics.

The OHDSI – OMOP Common Data Model is one such data model that allows for the systematic analysis of disparate observational databases and EMRs. The data from diverse systems needs to be extracted, transformed and loaded on to a CDM database. Once a database has been converted to the OMOP CDM, evidence can be generated using standardized analytics tools that are already available.

Each data source requires customized ETL tools for this conversion from the source data to CDM. The OHDSI ecosystem has made some tools available for helping the ETL process such as the White Rabbit and the Rabbit In a Hat. However, health data warehousing process is still challenging because of the variability of source databases in terms of structure and implementations.

Hephestus is an open-source python tool for this ETL process organized into modules to allow code reuse between various ETL tools for open-source EMR systems and data sources. Hephestus uses SqlAlchemy for database connection and automapping tables to classes and bonobo for managing ETL. The ultimate aim is to develop a tool that can translate the report from the OHDSI tools into an ETL script with minimal intervention. This is a good python starter project for eHealth geeks.

Anyone anywhere in the world can build their own environment that can store patient-level observational health data, convert their data to OHDSI’s open community data standards (including the OMOP Common Data Model), run open-source analytics using the OHDSI toolkit, and collaborate in OHDSI research studies that advance our shared mission toward reliable evidence generation. Join the journey! here

Disclaimer: Hephestus is just my experiment and is not a part of the official OHDSI toolset.

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Categories
Research Resources

McMaster’s start-up incubator to receive $1.2 million from FedDev Ontario

This article was first published on Daily News. Read the original article.

The Government of Canada, through FedDev Ontario, is providing McMaster with $1.2 million to expand The Forge, a collaborative makerspace where entrepreneurs can access advanced equipment to design and build innovative new products.

 

Forge

The Honourable Filomena Tassi, Minister of Seniors and Member of Parliament for Hamilton West-Ancaster-Dundas, made the announcement today on behalf of the Honourable Navdeep Bains, Minister of Innovation, Science and Economic Development and minister responsible for FedDev Ontario.

“FedDev Ontario’s funding is providing invaluable support to the innovation community in Hamilton,” said Tassi. “The government of Canada is proud to support McMaster — one of Canada’s premier research-intensive universities — to expand The Forge’s makerspace and allow more companies to develop and bring new products to market.”

The funding will allow The Forge to expand its makerspace as it moves into a 10,000 square-foot facility shared with partner Innovation Factory. It will also purchase additional 3D printers and other fabricating equipment, and increase support to entrepreneurs through mentoring. As a result, the number of companies supported will almost double from 24 to up to 40 annually, with up to 75 new jobs created as a result.

“This strategic investment from the Government of Canada will strengthen the entrepreneurial capacity of our region by providing McMaster’s students and the wider Hamilton community access to the centralized expertise and infrastructure so essential for creating start-ups and business growth opportunities,” said Karen Mossman, Acting Vice-President of Research at McMaster and chair of the McMaster Innovation Park board of directors.

More than 105 tech companies have graduated from The Forge since its founding in 2014, with more than 300 employees hired and $20 million of private and public investment raised.

The Forge’s expansion further enhances McMaster’s entrepreneurial ecosystem and reputation as a leader in developing innovative manufacturing assets, in particular within the McMaster Innovation Park, which is also home to the McMaster Automotive Research Centre (MARC) and the Centre for Biomedical Engineering and Advanced Manufacturing (BEAM).

This article was first published on Daily News. Read the original article.

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Resources

Oscar eForm Generator

OSCAR Eform Generator
OSCAR Eform Generator

Electronic capture of patient data is vital in any health information system. It ‘s hard to bundle every form that a clinician will ever need along with an EMR. The EMRs adopt various strategies to solve this problem, but a general standard is lacking.

Eforms is OSCAR’s solution to this problem. The OSCAR eForms are arguably one of the most useful features of OSCAR and is being used in many settings beyond which it was initially designed for. Community eForms can be downloaded from the OSCAR Canada Users Society.

EForm is not an elegant solution and creating complex eforms require programming expertise. Reporting of data collected through eForms is difficult because of the way in which the data is abstracted as key-value pairs in the database.

Oscar provides basic eForm generator functionality built-in using a form image in the background with controls transposed on top. However, it is not user-friendly and lacks the ability to save and continue the work later.

Oscar EForm Generator

I have created an online OSCAR eForm generator that solves most of the above-mentioned problems. Here is an advanced OSCAR eform generator with drag and drop controls. You can save the form as a text file and continue editing later after loading the content. It also supports radio-buttons by internally mapping to OSCAR supported code. You can pull OSCAR demographic fields and define complex show/hide rules. You can cut and paste the generated code into the OSCAR eform editor. The form is generated in your browser using javascript and it is not sent or saved on our server.

Watch the video below to see how it is done. This is still being tested and is not ready for production. Contact us for more details. Please report bugs, function requests, and feed backs.

The application is available here: http://nuchange.ca/oscar-eform-generator .