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The Eliyahu Project Menachem Elyah Paull · published as Mark E. Paull מנחם אליה פאל DOWNLOAD THE APPLICATION Install The Eliyahu Project on your phone

Clinical Research

What the data never recorded.

Clinical AI is trained on outcomes. Patients live in decisions. My research is about the layer in between — the state, context, uncertainty and timing behind each clinical decision, none of which survives into the record.

Peer reviewer and published author, Diabetes Care (American Diabetes Association). Living with Type 1 diabetes since 1967.

Peer-reviewed publications

Temporal Discontinuity in Continuous Glucose Monitoring: How Midnight Segmentation Generates Systematic Measurement Artifact

Diabetes Technology & Therapeutics · Brief Report, OnlineFirst, 23 March 2026

Calendar-based CGM segmentation misaligns with continuous circadian glucose oscillators. Circular time representation and Shannon entropy analysis show midnight segmentation produces a 2.8-fold reduction in continuity correlation and 12.1% information loss.

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Seventeen Alarms at 3 A.M.: Environmental Trauma During Hospital Care for Diabetic Ketoacidosis

Diabetes Care · 2026;49(4):540–541

Simultaneous hospital alarms elevate cortisol and directly counteract insulin effectiveness in DKA. Argues for environmental audit and sensory-aware design as patient-safety interventions.

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What My Continuous Glucose Monitor Can Never Capture

STAT News · 8 December 2025

CGM systems fail to capture the behavioural and cognitive context behind glucose variability — and physiological data alone does not reflect adherence or clinical intent.

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Frameworks

I

ESP-360° Decision-Aware CGM Dataset

A novel annotated dataset pairing continuous glucose monitoring signals with real-time cognitive decision context: 536 records, 341 structured variables and 21 human-state annotation layers.

II

Decision Shadow / Decision Provenance

Formalises how prior clinical decisions generate persistent interpretive biases in AI-assisted diagnosis, with measurable properties — depth, overlap and distortion — applicable across CGM, otolaryngology, ophthalmology and anaesthesia.

III

The Missing Constraint Layer

Identifies the systematic absence of behavioural and cognitive context as a structural flaw in medical AI training pipelines, with direct implications for patient safety when clinician judgment is iteratively encoded as error.

IV

ESP-360° Human-State Decision Architecture

A multi-layer framework maintaining simultaneous contradictory interpretations to prevent automation bias while preserving non-delegable human authority. U.S. provisional patent, October 2024.

Collaborators

Leo Anthony Celi, MD — Senior Research Scientist, MIT and Harvard Medical School. Jack Shahin, MD, FRCSC — University of Toronto.

Available for academic partnerships, peer review, speaking engagements and media inquiries. Full record at ORCID · 2025 CME record · Substack.