harpIA is our proprietary Artificial Intelligence system which analyzes radiology reports through Natural Language Processing (NLP) and extracts extremely important information from within a non-structured text. The system is trained with over 3 million medical reports and is capable of differentiating and identifying the main medical concepts such as findings, anatomic structures and pathologies.
harpIA BI systems enables you to create a case analysis dashboard based on the results within the report, according the radiologists assessment. The occurrence of any findings within radiological reports may be mapped and quantified and compared to other data from the institution. Once important data is extracted from a report, the database becomes semantic, allowing a search based on pathologies and not just by exam type. This streamlines the search and change information into knowledge.
Medical reports may be reviewed on a line-by-line basis in real time in order to identify positive phrases for pathologies in addition to warnings for important pathologies which may originate automatic workflows associated with customer protocols, and also warnings for potential incongruencies such as contrast/laterality/sex.
By simply sending the texts of medical reports or even their PDF files, harpIA makes all data anonymous according to the local privacy laws and, within seconds, generates the results of each report. Such analysis may be promptly accessed in the hospital´s current system through APIs or even through NeuralMed’s online portal.
Yes, as Simple as that.
Alignment between the hospital staff and NeuralMed teams concerning how data will be sent and returned
NeuralMed follows the first exams sent and the data sent back, according to the integration manual, revealing the first results
Take immediate advantage of exams analyzed through AI in your service workflow
harpIA automatically identifies potential incongruencies related to laterality, sex or even use of contrast in the medical reports as well as detecting the critical findings before final submission. The patient´s previous exams may be sorted based on findings, reducing time spent searching for significant previous exams.
As medical report data is automatically structured using AI, the management sector can gather information on a unit, doctor or even a patient, optimizing resources to be allocated, improve quality control and predict future requests.
Hospitals and clinics utilizing harpIA dedicate more time to diagnostics, which allows doctors to focus on the patient's health and not on the system's data.