Our Technology

Innovative Medical AI & FHIR-Native Cancer Registry Technology.

Our foundation is built on deep expertise.

Our founders spent years at IBM Watson, and that legacy is reflected in our sophisticated approach to medical AI. We don’t just use AI; we build medical language models and extend existing medical ontologies to solve the unique challenges of oncology data.

While the UMLS (Unified Medical Language System) is a foundational tool with over 130 source vocabularies, its internal inconsistencies often lead to data gaps. NeuralFrame provides a more rigorous solution. By labeling unstructured medical text with precision, we’ve developed a unique Knowledge Iteration Engine and domain-specific CORE Models. These innovations go beyond traditional medical NLP (Natural Language Processing) to deliver unmatched accuracy.

As we ingest more data, our medical AI becomes increasingly powerful, utilizing both explicit and implicit feedback. Our expert-weighted knowledge graphs and state-of-the-art language models allow for rapid adaptation, keeping NeuralFrame at the cutting edge of oncology AI innovation..

This may all sound great, but what does it mean in the real world? Well, here’s a for-instance: When we analyze usage statistics from our industry-leading cancer registry product, KACI, we find the following time savings for ODS’s in abstracting cases from the EMR:

What does this advanced technology look like in practice? When we analyze usage statistics from KACI, our industry-leading cancer registry software, the impact on Oncology Data Specialists (ODS) is clear. KACI’s fast and accurate automatic abstraction frees up ODS’s to focus on complex analysis and reporting instead of hunting through synoptics reports and other structured and unstructured medical documents.

This observation about KACI brings us to a final thought on NeuralFrame’s approach to medical data. Founded in 2017, we brought together an expert team of clinicians, systems engineers, and AI specialists to build better products for the medical community, with AI at the core. KACI is not a software application with an AI engine retrofitted as a bolt-on. KACI, and every product that comes from NeuralFrame’s software lab, has been engineered from the ground up around a deep understanding of the integration of AI with medical data. By building our products with AI as the core foundation rather than as an afterthought, we are able to deliver a seamless and uniquely valuable experience for healthcare professionals.

Drinking from the FHIR Hose.

Next-generation architecture. Massive record counts.

The Fast Healthcare Interoperability Resources (FHIR). standard, developed by HL7, is the backbone of modern healthcare IT. By utilizing FHIR-native architecture, NeuralFrame ensures that your data is not just stored, but is actionable and interoperable.

The benefits of using FHIR to exchange data with EMR systems are manifold. FHIR’s standardized data models provide a consistent and structured way to represent clinical information. This consistency enhances data quality and accuracy. Furthermore, FHIR is fast. Its RESTful APIs allow for efficient data retrieval, searching, and updating, leading to timely reporting. And let’s face it, the sooner you can report medical data, the more likely your data will be useful to the designers of clinical trials, and the patients they serve. In this business, saving time means saving lives.

All NeuralFrame products are FHIR-native, meaning that our systems architecture has been designed from the get-go with FHIR interoperability in mind. The result is that we can use FHIR to connect with all relevant EMR resources, from your primary EMR to specialty EMR and other diagnostic sources for radiation, surgery, systemic therapy, and pathology. Every week, NeuralFrame automatically ingests millions of EMR records for its customers (see our landing page for the latest counts for this week). These records are then passed through our proprietary medical AI models (see section on AI above) to identify Casefinding and Follow-up data. Combined with KACI, our cancer registry software product, the benefits are immediately apparent:

Casefinding

ODS Workflow Improvement

Follow-up

Registry Management

Casefinding – KACI’s EMR integration directly accesses pathology reports, eliminating the need for separate pathology surveillance software. KACI combines pathology with other EMR resources from the clinic and billing to deliver the most accurate records possible, removing duplicates and not-reportables, without missing cases. KACI automation typically reduces Casefinding time by more than 80%.

ODS Workflow Improvement – After searching patient records, the Casefinding process captures and pre-populates circa 40% of the data fields, reducing manual input time and eliminating transcription errors. Since gains in this area impact the entire ODS team, even a conservative estimated efficiency gain of 12% delivers significant economic benefit.

Follow-up – Follow-up processes that require manual effort are expensive and prone to backlog. KACI integrates multiple EMR resources, including external resources such as Epic’s Care Everywhere, to update Date-of-Last-Contact. The integrated Social Security Death Index (Death Master File – DMF) provides timely updates for expired patients. According to the NCRA Workforce Study, Follow-up at the average hospital requires 2.5 FTE per 6,000 new diagnoses. KACI reduces Follow-up labor by 80-90%.

Registry Management – Hospital workflows that employ manual processes cost significant registry management time. KACI’s EMR integration reduces QA issues, saving management time. In addition, KACI’s QA dashboards allow ODS’s to self-check. KACI integrates case assignment and abstract notes to eliminate spreadsheets. Users can save up to 90% of case review time.

A Strategic Partnership for the Future.

The ever-expanding cloud.

NeuralFrame is more than a software provider; we are a strategic partner for the largest healthcare organizations in North America. We help institutions future-proof their registry requirements by providing a scalable, cloud-based data backbone.

Our expertise in applying advanced medical language models and leveraging the power of FHIR enables these organizations to unlock the full potential of their data. Here are some of the ways we are helping our customers to adapt and thrive in the rapidly evolving healthcare landscape:

Patient Outcomes – Monitor outcomes and treatment responses for life-science research.

Data Warehousing – Provide rich, structured datasets to academic analytics departments via nightly SQL-ready exports.