Genetic Evidence

Overview

In the modern era of medical genetics, a definitive diagnosis for a rare inherited disorder almost always culminates in advanced genetic testing. Whether a physician orders a targeted multi-gene panel, Whole Exome Sequencing (WES), or chromosomal microarray analysis, the ultimate result is delivered by a highly specialized commercial or academic laboratory. However, exactly like standard clinical notes and basic laboratory values, these complex genetic results are overwhelmingly delivered back to the ordering physician as static, flattened PDF documents. These documents are notoriously dense, often spanning 20 to 30 pages filled with highly technical variant nomenclature, complex molecular interpretations, and extensive bibliographical references. Sanjeevni’s Natural Language Processing engines have been specifically tuned to ingest and parse these highly specialized genetic PDFs. When a laboratory report is uploaded into the patient's secure workspace, the AI systematically scans the document to extract the critical genetic entities. It identifies the specific genes implicated (e.g., FBN1, MYBPC3, COL1A1), extracts the precise molecular nomenclature of the detected variants, determines the zygosity of the findings, and crucially, extracts the clinical classification provided by the sequencing laboratory. By structuring this genetic data, Sanjeevni ensures that the ultimate piece of diagnostic evidence is not lost in a sea of PDF text. The extracted variants and their corresponding classifications are elevated directly to the physician's Case Dashboard, clearly displayed alongside the patient's phenotypic profile. This prevents critical genetic findings from being overlooked during rushed clinical reviews and ensures that the structured data can be easily exported via FHIR API to the hospital’s central Electronic Health Record.