Epidexia

Research

01

Does Adaptive PM2.5 Correction Transfer Across Devices, Sites, and Time? A Prospectively Frozen Three-Role PurpleAir Evaluation

IEEE ICOCO 2026 · Accepted with revision

Low-cost PurpleAir sensors need correction before their PM2.5 readings can be trusted, and adaptive corrections look excellent on the data they were fitted to. This paper asks whether that correction still holds on a new device, at a new site, and a year later. Using a prospectively frozen three-role protocol that fixes the model, the evaluation, and the held-out roles before any test data is seen, it measures transfer honestly and reports the negative findings alongside the positive ones.

Air quality, Sensor calibration, Evaluation protocols
Preprint forthcoming
02

ADNET: Dual-Stream Alzheimer's Diagnosis Network with Integrated Grad-CAM Explainability

IEEE IATSMI 2025 · Preprint on TechRxiv, October 2025

ADNET is a dual-stream convolutional network that stages Alzheimer's disease from a single MRI slice, from cognitively normal through early, mild, and late impairment to AD. By pairing two parallel feature streams with Grad-CAM heatmaps of the regions behind each decision, it reaches 97.55% test accuracy while showing clinicians exactly where it looked, so a prediction can be checked rather than trusted.

Deep learning, Neuroimaging, Explainability
Read the paperdoi:10.36227/techrxiv.175987989.93553390/v1
03

A Leakage-Safe Temporal Benchmark for Target-Disease Prioritization: Explaining Network Uplift through Local Support Overlap

IEEE BIBM 2026 · Accepted short paper

A benchmark for ranking which disease targets to pursue next, built so that no future knowledge leaks into training because the temporal split is enforced rather than assumed. Evaluated on it, the gains that network methods show over simpler baselines trace back to a single measurable cause: how much local support a candidate pair already has in the graph. Accepted as a short paper at IEEE BIBM 2026 at a 19.48% acceptance rate.

Benchmarks, Network biology, Target prioritization
Preprint forthcoming