Clinical AI

Temporal clinical reasoning

Longitudinal laboratory intelligence

A clinical data pipeline and interpretable reasoning layer for detecting meaningful changes across a patient's laboratory trajectory.

Time seriesData engineeringAKIDILI
01 · Problem

Laboratory results arrive from heterogeneous systems as isolated values. Clinicians need reliable trajectories connected to medication exposure and patient context.

02 · My role

Architected the ingestion model, normalization logic, incremental synchronization, validation, monitoring, and temporal reasoning layer.

03 · System

Patient- and admission-level time series with idempotent upserts, batch processing, data-quality checks, and interpretable risk signals.

04 · Scale

2M+ laboratory records spanning more than 50 biomarkers.

05 · Evidence

Source-level validation, explicit temporal alignment, reproducible transformations, and clinician-interpretable signal logic.

06 · Outcome

A foundation for earlier recognition of AKI, DILI, infection, and evolving clinical deterioration without hiding the underlying trajectory.

Next case study

Hospital-system integration