The next generation of oncology data management software is here!
The wait is over. At last, an oncology data management software delivers savings opportunities and process efficiencies to the cancer registry. NeuralFrame has developed KACI (Knowledge Assistant for Clinical Information), the cutting-edge cloud-based system built by leading clinicians, CTRs, and software engineers to provide fast, accurate data to fulfill registry requirements and deliver timely information to clinicians, researchers, and administrators, essential for providing outstanding patient care.
What people are saying about KACI
“The ’one to watch’”
A.W.
Tumor Registrar, Oncology Analytics
“It’s a game changer”
A.R.
Cancer Program Specialist
“Easy-to-use report function”
E.V.
CTR.
“KACI has a lot of improved and added functions that others don’t have”
E.E.
Data Quality Associate
“It provides the format and data tools that registrars need to perform organized, quality work with ease and timeliness”
G.S.
CTR
“I can see KACI having the ability to make registry abstracting a more efficient process with the potential to produce more meaningful data reports”
S.A.
Cancer Registry Manager
“KACI is set up in a logical order and is very clear”
S.M.
Supervisor, Cancer Registry
“KACI has updated fields and background resources where my current software does not”
D.J.
Manager, Tumor Registry and Accreditation
The KACI Difference
Natural Language Processing
KACI’s Natural Language Processing (NLP) automatically extracts field values from synoptics reports and other structured medical documents. KACI integrates guidelines from multiple standard-setters into a single up-to-date source. This leading-edge technology facilitates fast accurate abstracting, freeing CTRs to focus on complex analysis and reporting.
Easy Abstraction
Unique Import Process
KACI’s unique import process for casefinding reduces manual entry, reviews, and duplication of cases.
Streamlined Interface
The streamlined user interface facilitates abstraction.
Edits Correction
KACI automatically identifies edits to be corrected.