30 posts tagged with "frontend"

Every research platform hits the same inflection point. You build a powerful cohort builder. Researchers love it. They create cohorts for Study 1, Study 2, the rare disease project, the pancreatic cancer corpus. Each study gets its own "All-Cause Death" outcome. Each gets its own "MACE" composite endpoint. Before long, you're staring at 89 cohort definitions in a flat, unsorted list where a meticulous seven-concept-set new-user design sits next to an auto-generated stub with one concept and no generations. A Rett syndrome genotype-stratified trial cohort is sandwiched between a SynPUF cardiometabolic triad and a never-run hypertension bundle. The list is technically complete and practically useless.

Today, Parthenon ships a cohort categorization system that solves this. We audited every cohort definition in the database, identified and consolidated 9 duplicates and orphans, assigned 80 surviving cohorts to 8 clinical domains, computed a quality tier for each one, and rebuilt the Cohort Definitions page with collapsible domain-grouped sections and quality filter pills. Researchers can now browse by clinical domain, filter to study-ready phenotypes, and find what they need in seconds instead of scrolling through a flat table.

This post describes the problem in detail, explains how we analyzed and scored the inventory, walks through the architecture, and shows what the result looks like.

A dense day on Parthenon with 19 commits focused on three interlocking themes: hardening Abby's ChromaDB knowledge substrate, broadening test coverage across the UI and service layer, and tying up the loose ends needed to ship v1.0.4 cleanly. No single flashy feature today — just the kind of careful, compounding work that makes a platform trustworthy.

The Patient Profile's Labs Panel has been one of Parthenon's persistent frustrations: a table with Ranges and Status columns that were perpetually empty, and a display format that forced clinicians to mentally reconstruct a lab value's trajectory from a column of numbers. Today we shipped the fix — a Recharts line chart with a shaded reference-range band, status-colored measurement dots, and a hybrid data layer that finally makes lab reference ranges work across every CDM source.

We shipped eight analytical upgrades to the Patient Similarity Engine last week — hierarchical concept similarity, Love plots, distributional divergence, propensity score matching, UMAP projections, temporal DTW, consensus clustering, and similarity network fusion. The engine is now, arguably, more analytically capable than anything in the OHDSI ecosystem for cohort-level comparison.

But the UI was still the original five-tab layout we built in the first sprint. And no amount of analytical horsepower matters if a researcher opens the page, sees five tabs without context, and doesn't understand the order of operations.

Tonight we replaced it entirely.

A landmark day for platform observability and data pipeline reliability. We shipped a fully wired Jobs monitoring page that surfaces all 13+ tracked job types, broke through a major ETL performance ceiling on the SynPUF dataset (17 hours → 14 minutes for drug_era builds), and closed out a cohort generation audit that uncovered eight discrete bugs across the SQL builders, API layer, and frontend.

A massive day on the ingestion front — 87 commits landed in Parthenon today, almost entirely focused on building out a brand-new end-to-end data ingestion pipeline. We now have a fully wired system for creating ingestion projects, uploading raw files, staging them into a schema-isolated PostgreSQL environment, and handing off to Aqueduct for ETL. This has been a long time coming.

A massive day on Parthenon with 193 commits landing across the platform. The headlining work: a near-complete publication/manuscript workflow that takes study analyses all the way to a formatted, auto-numbered document preview, plus a long-overdue rename of the R Analytics Runtime to Darkstar — the name it's been running under in Docker all along.

Today was one of those satisfying days where two major workstreams converged: we pushed the Ares data quality module from skeleton to a fully featured analytics suite with four distinct intelligence phases, and we permanently fixed a cluster of compounding bugs that had been making Achilles characterization runs fragile on large real-world datasets. Both efforts move Parthenon meaningfully closer to being a production-grade OHDSI research platform.

After months of a perpetually red CI pipeline, today marks a turning point for Parthenon: 92 commits, a full-spectrum codebase review, a complete AtlanticHealth patient synthesis pipeline, and — most satisfying of all — every CI job green. Here's how we got there.

A big architectural day on Parthenon: we shipped the new Workbench launcher experience and drafted the formal plan to collapse our multi-database mess into a single, schema-isolated parthenon database. A noticeably cleaner codebase on the other side.