The NHOS Children's Symptoms Checker™ (NHOS-CSC) is a fully client-side pediatric symptom-triage artifact released as informational research software. It is designed to answer a narrow methodological research question: can a compact, fully inspectable, browser-local pediatric symptom-triage tool expose its assumptions and computational pathway sufficiently for independent audit, replication, and critique — while still delivering a graded, safety-first triage recommendation? This release (v4.0.0) documents the artifact, its nine-module clinical upgrade pack, and its proposed validation framework. What the artifact is NHOS-CSC is architected for fully client-side execution: all inference runs locally within the client runtime, with no server-side inference, no hosted API dependency, and no embedded analytics. Its knowledge base — 3,392 unique pediatric conditions and 591 clinically weighted symptom attributes across 17 body systems — is parsed and indexed at application startup. Its inference engine implements a Naive Bayes classifier in log-space with age-aware condition filtering, explicit negative-evidence handling, a small co-occurrence adjustment, and posterior normalization. Output is a discrete 50-level Triage Severity Score (0–49) mapped to six clinically meaningful care bands: Self-Care, Routine, Soon, Urgent, Emergency, and Emergency-Ambulance. A mandatory 19-question red-flag screen intercepts life-threatening presentations before any statistical inference occurs. What is new in v4.0.0 — the Complete Clinical Upgrade Pack Version 4.0.0 introduces a nine-module Complete Clinical Upgrade Pack composed through an additive composition layer that wraps four well-defined core extension points without modifying the underlying inference, scoring, or knowledge-base modules. Zero lines of the core application are modified. The upgrade is fully reversible by removing a single add-on layer and is fully configurable through a single public configuration object exposing 13 documented tuning parameters. The nine modules are: Pediatric Vitals Interpretation Engine — age-banded physiological reference ranges across six pediatric cohorts (neonate, infant, toddler, preschool, school-age, adolescent) for heart rate, respiratory rate, systolic blood pressure, temperature, and peripheral oxygen saturation. Critical vitals readings escalate the triage score through hard constraints. Expanded Red-Flag Detection — the mandatory pre-inference safety screen expands from 9 to 19 binary questions, adding bulging fontanelle, petechiae, stridor, lethargy, poor neonatal feeding, toxic appearance, bilious vomiting, bloody stool, active seizure, and purpura. Developmental Milestone Reference — 16 age-matched milestone bands from 1 month to 17 years, displayed within a configurable ±2-year window around the child's age. Medication Safety Layer — 8 age-filtered medication entries with weight-aware dosing context and hard-coded aspirin contraindication for children under 16. Parental Guidance UX Layer — plain-language actionable guidance translating triage output into immediate steps and emergency escalation criteria. Clinician Dashboard Modal — a single-view clinical summary combining organ-system heatmap, ranked differential (top 6), vitals flags, predictive indices, and case timeline. Four Predictive Risk Indices — heuristic 0–10 screening scores covering early sepsis risk, respiratory distress, dehydration, and febrile illness risk. Explain-This-Result Panel — a plain-language "Why this band?" panel surfacing the top 2–5 contributing factors behind the assigned triage band. Clinical Content Versioning System — nine independent content version tracks that separate clinical knowledge versions from software release versions, enabling independent audit and staged clinical-content upgrades. Architecture and reproducibility The artifact preserves every architectural guarantee of the prior releases: client-side-only execution, zero server dependency, full inspectability, and no telemetry. All processing — condition parsing, symptom indexing, red-flag screening, vitals interpretation, Bayesian inference, triage scoring, milestone generation, medication filtering, guidance generation, predictive index computation, explanation reason extraction, and content versioning — executes locally within the client runtime. The only network requests are optional presentation resources (fonts, icons, and visualization libraries); none of them receive user inputs. A runtime library audit is emitted on application startup, reporting declared design targets versus actual loaded counts for every headline metric. The Triage Severity Score is fully specified by six base values, five adjustment terms, five hard constraint rules (including one vitals-derived), one integer clamp, six band boundaries, and eight vitals escalation thresholds — enabling bit-exact independent reproduction. What the artifact is not This artifact is not a medical device and is not cleared or approved by the FDA, EMA, MHRA, TGA, or any other regulatory authority. It has not been evaluated in a prospective clinical trial, subjected to retrospective chart review, validated against a gold-standard vignette set, or calibrated against clinical outcomes. The probabilities, rankings, and triage recommendations produced by the model are model-derived quantities, not clinically calibrated performance measures. They must not be interpreted as diagnostic, prognostic, or therapeutic guidance. In any emergency, contact emergency services immediately — 911 (US) · 999 (UK) · 112 (EU) · 000 (AU) — regardless of what this artifact displays. What this deposit contains The Zenodo record for this release contains the reference implementation of the artifact plus the Complete Clinical Upgrade Pack, the machine-readable condition and symptom libraries, the configuration schema reference, the triage-score specification, the vitals reference range specification, the milestone band specification, the medication reference specification, the predictive risk index specification, the clinician dashboard specification, the explain-this-result specification, the content versioning specification, the proposed validation protocol, the technical white paper (PDF and Markdown), a README with execution and tuning instructions, and license files (MIT for code; CC BY 4.0 for documentation). Intended use The artifact is offered as: An informational triage aid for parents and caregivers. A teaching artifact for health informatics and medical education. A reproducible research baseline for symptom-checker methodology. A transparent pediatric baseline for comparative evaluation. A worked example of client-side clinical decision support with integrated interactive visualization. It is explicitly not intended for diagnosis, replacement of clinical judgment, use as a regulated clinical workflow, or population-level epidemiological inference. Citation and licensing Software code is released under the MIT License. Documentation and research text are released under Creative Commons Attribution 4.0 International (CC BY 4.0). This artifact should be cited as software and methodology research. Its future scientific value will depend on independent review, empirical validation, calibration analysis, and transparent reporting of both successful and unsuccessful results.
Inc. NHOS Labs, Adedapo Ogundiran· Zenodo (CERN European Organi...· 0 citations
The NHOS Children's Symptoms Checker™ (NHOS-CSC) is a fully client-side pediatric symptom-triage artifact released as informational research software. It is designed to answer a narrow methodological research question: can a compact, fully inspectable, browser-local pediatric symptom-triage tool expose its assumptions and computational pathway sufficiently for independent audit, replication, and critique — while still delivering a graded, safety-first triage recommendation? This release (v4.0.0) documents the artifact, its nine-module clinical upgrade pack, and its proposed validation framework. What the artifact is NHOS-CSC is architected for fully client-side execution: all inference runs locally within the client runtime, with no server-side inference, no hosted API dependency, and no embedded analytics. Its knowledge base — 3,392 unique pediatric conditions and 591 clinically weighted symptom attributes across 17 body systems — is parsed and indexed at application startup. Its inference engine implements a Naive Bayes classifier in log-space with age-aware condition filtering, explicit negative-evidence handling, a small co-occurrence adjustment, and posterior normalization. Output is a discrete 50-level Triage Severity Score (0–49) mapped to six clinically meaningful care bands: Self-Care, Routine, Soon, Urgent, Emergency, and Emergency-Ambulance. A mandatory 19-question red-flag screen intercepts life-threatening presentations before any statistical inference occurs. What is new in v4.0.0 — the Complete Clinical Upgrade Pack Version 4.0.0 introduces a nine-module Complete Clinical Upgrade Pack composed through an additive composition layer that wraps four well-defined core extension points without modifying the underlying inference, scoring, or knowledge-base modules. Zero lines of the core application are modified. The upgrade is fully reversible by removing a single add-on layer and is fully configurable through a single public configuration object exposing 13 documented tuning parameters. The nine modules are: Pediatric Vitals Interpretation Engine — age-banded physiological reference ranges across six pediatric cohorts (neonate, infant, toddler, preschool, school-age, adolescent) for heart rate, respiratory rate, systolic blood pressure, temperature, and peripheral oxygen saturation. Critical vitals readings escalate the triage score through hard constraints. Expanded Red-Flag Detection — the mandatory pre-inference safety screen expands from 9 to 19 binary questions, adding bulging fontanelle, petechiae, stridor, lethargy, poor neonatal feeding, toxic appearance, bilious vomiting, bloody stool, active seizure, and purpura. Developmental Milestone Reference — 16 age-matched milestone bands from 1 month to 17 years, displayed within a configurable ±2-year window around the child's age. Medication Safety Layer — 8 age-filtered medication entries with weight-aware dosing context and hard-coded aspirin contraindication for children under 16. Parental Guidance UX Layer — plain-language actionable guidance translating triage output into immediate steps and emergency escalation criteria. Clinician Dashboard Modal — a single-view clinical summary combining organ-system heatmap, ranked differential (top 6), vitals flags, predictive indices, and case timeline. Four Predictive Risk Indices — heuristic 0–10 screening scores covering early sepsis risk, respiratory distress, dehydration, and febrile illness risk. Explain-This-Result Panel — a plain-language "Why this band?" panel surfacing the top 2–5 contributing factors behind the assigned triage band. Clinical Content Versioning System — nine independent content version tracks that separate clinical knowledge versions from software release versions, enabling independent audit and staged clinical-content upgrades. Architecture and reproducibility The artifact preserves every architectural guarantee of the prior releases: client-side-only execution, zero server dependency, full inspectability, and no telemetry. All processing — condition parsing, symptom indexing, red-flag screening, vitals interpretation, Bayesian inference, triage scoring, milestone generation, medication filtering, guidance generation, predictive index computation, explanation reason extraction, and content versioning — executes locally within the client runtime. The only network requests are optional presentation resources (fonts, icons, and visualization libraries); none of them receive user inputs. A runtime library audit is emitted on application startup, reporting declared design targets versus actual loaded counts for every headline metric. The Triage Severity Score is fully specified by six base values, five adjustment terms, five hard constraint rules (including one vitals-derived), one integer clamp, six band boundaries, and eight vitals escalation thresholds — enabling bit-exact independent reproduction. What the artifact is not This artifact is not a medical device and is not cleared or approved by the FDA, EMA, MHRA, TGA, or any other regulatory authority. It has not been evaluated in a prospective clinical trial, subjected to retrospective chart review, validated against a gold-standard vignette set, or calibrated against clinical outcomes. The probabilities, rankings, and triage recommendations produced by the model are model-derived quantities, not clinically calibrated performance measures. They must not be interpreted as diagnostic, prognostic, or therapeutic guidance. In any emergency, contact emergency services immediately — 911 (US) · 999 (UK) · 112 (EU) · 000 (AU) — regardless of what this artifact displays. What this deposit contains The Zenodo record for this release contains the reference implementation of the artifact plus the Complete Clinical Upgrade Pack, the machine-readable condition and symptom libraries, the configuration schema reference, the triage-score specification, the vitals reference range specification, the milestone band specification, the medication reference specification, the predictive risk index specification, the clinician dashboard specification, the explain-this-result specification, the content versioning specification, the proposed validation protocol, the technical white paper (PDF and Markdown), a README with execution and tuning instructions, and license files (MIT for code; CC BY 4.0 for documentation). Intended use The artifact is offered as: An informational triage aid for parents and caregivers. A teaching artifact for health informatics and medical education. A reproducible research baseline for symptom-checker methodology. A transparent pediatric baseline for comparative evaluation. A worked example of client-side clinical decision support with integrated interactive visualization. It is explicitly not intended for diagnosis, replacement of clinical judgment, use as a regulated clinical workflow, or population-level epidemiological inference. Citation and licensing Software code is released under the MIT License. Documentation and research text are released under Creative Commons Attribution 4.0 International (CC BY 4.0). This artifact should be cited as software and methodology research. Its future scientific value will depend on independent review, empirical validation, calibration analysis, and transparent reporting of both successful and unsuccessful results.
Inc. NHOS Labs, Adedapo Ogundiran· Zenodo (CERN European Organi...· 0 citations
NHOS Oracle Matrix Search Engine™: A Local Hybrid Retrieval and Contextual Discovery Architecture for Personal Health Knowledge Technical Research White Paper — Version 1.2 · September 2026Corresponding Software Version: NHOS Oracle Matrix Search Engine v8.0.0Research Stage: Implemented Research System & Validation Framework NHOS Labs, Inc. — NHOS Intelligence Matrix Engine™ Research Program Overview This technical research white paper presents the architecture, retrieval methodology, implementation model, and planned empirical validation framework of the NHOS Oracle Matrix Search Engine™, a local hybrid retrieval and contextual discovery subsystem developed within the NHOS Intelligence Matrix Engine™ (NIME™) Research Program. Oracle is designed as a structured "front door" to NHOS health knowledge. Rather than relying on a single retrieval mechanism, the engine combines exact and content matching, title and excerpt weighting, token-level matching, Levenshtein-based fuzzy matching, category weighting, type-specific ranking, multi-concept query processing, and contextual discovery. The architecture is deliberately non-semantic and non-ML-based. Core retrieval does not depend on embeddings, vector databases, large language models, or remote inference. The system is designed for local, offline-capable execution, supporting privacy-conscious health-information discovery while minimizing dependence on external services. Research Contribution The Oracle research program investigates whether a deterministic, hybrid retrieval architecture can provide effective and reproducible retrieval across heterogeneous personal-health knowledge while retaining local execution and explicit system provenance. The research emphasis is therefore not simply on implementing a search interface, but on experimentally evaluating the contribution of individual retrieval mechanisms and their combined effect on retrieval quality. The validation framework is designed to investigate: retrieval relevance; precision and recall; ranking quality using MRR and nDCG; confidence behavior and calibration; contribution of individual retrieval mechanisms through ablation studies; comparison with conventional retrieval baselines; query-stratum performance; latency and computational behavior; scalability; retrieval error patterns; privacy and network behavior; voice-query equivalence; and reproducibility across documented software, corpus, configuration, and runtime versions. Implemented Architecture Version 1.2 documents the evolution of Oracle from software v6.3 through v8.0.0, including the following implemented capabilities: Configuration-driven retrieval.Scoring constants, routing triggers, and runtime limits are exposed through a versioned ORACLE_CONFIG structure, supporting reproducible configuration and controlled experimentation. Hybrid retrieval.The engine combines exact/content matching, token matching, Levenshtein-based fuzzy matching, title/excerpt weighting, category weighting, and type-specific ranking. Multi-concept processing.Queries containing multiple concepts can be decomposed and processed across the heterogeneous NHOS knowledge corpus. Deterministic recommendation mode.Hash-seeded candidate selection replaces uncontrolled randomization, enabling reproducible recommendation experiments. Parameter-free rank-based confidence.The default confidence method uses rank-based confidence rather than assuming that raw retrieval scores are directly comparable across queries. Runtime provenance.Engine, schema, corpus, and configuration metadata are exposed through the public JavaScript API, including NHOSOracleHybridSearch.getStats(). Embedded regression testing.The v8.0.0 distribution includes ten executable pure-function assertions covering core retrieval behavior; the shipped release reports 10/10 tests passed. Corpus integrity verification.External corpus files can be verified against recorded SHA-256 hashes before ingestion. HL7 FHIR R4 export.The engine provides a FHIR R4 Bundle export with resource-specific attributes and provenance metadata. Internationalization.The interface includes English, Spanish, French, and German language dictionaries using a data-driven internationalization mechanism. Voice retrieval interface.Browser-native Web Speech API integration supports voice-query input with interim transcript handling and language-aware processing. Strict-CSP modular distribution.The engine is distributed both as a self-contained single-file implementation and as a modular HTML/CSS/JavaScript implementation compatible with strict Content-Security-Policy environments. Validation Status The Oracle system described in this publication is an implemented research system accompanied by a defined validation framework. The white paper does not claim that Oracle has already demonstrated superior retrieval effectiveness, superior recommendation quality, calibrated confidence, clinical effectiveness, superior speech-recognition accuracy, or improved health outcomes. Those claims require empirical investigation. The planned evaluation, scheduled for Q4 2026–Q2 2027, will use controlled benchmark queries, predefined relevance judgments, baseline comparisons, ablation experiments, latency measurements, and reproducible execution conditions. This distinction between implemented capability and empirically demonstrated performance is intentional and central to the research program. Software Correspondence Paper version: 1.2Oracle Engine: 8.0.0Knowledge Schema: 1.0.0Corpus: 1.0.0Confidence Method: rank-basedInterface Languages: English, Spanish, French, GermanBuild Date: 11 September 2026 Runtime provenance is available through: NHOSOracleHybridSearch.getStats() The embedded regression harness is available through: NHOSOracleHybridSearch.runTests() The v8.0.0 release reports 10/10 regression assertions passed. Companion Software The corresponding v8.0.0 Oracle engine is deposited separately as companion software. Distribution entry points include: oracle_upgraded.html — self-contained single-file implementation oracle/oracle_upgraded.html oracle/oracle.css oracle/oracle.js — modular strict-CSP distribution Core retrieval requires no server, build system, or network connection. Research and Collaboration Use This publication is intended as a technical reference for researchers, engineers, health-informatics investigators, clinical and institutional collaborators, technology evaluators, and prospective research partners interested in: health-information retrieval; local-first computing; privacy-conscious health technology; hybrid lexical retrieval; fuzzy and multi-concept search; structured health knowledge; provenance-aware system design; reproducible retrieval experiments; and evaluation of deterministic intelligence architectures. The system is positioned as a research platform from which controlled empirical studies can be conducted. Future evaluation results will be reported separately from this architectural publication. Research Principle Build transparently. Measure rigorously. Report proportionally. NHOS Labs, Inc.NHOS Intelligence Matrix Engine™ Research ProgramNHOS Oracle Matrix Search Engine™Technical Research White Paper v1.2 · September 2026 Keywords health information retrieval; hybrid retrieval; fuzzy matching; Levenshtein distance; local-first software; personal health knowledge; knowledge discovery; domain-aware ranking; multi-concept search; contextual discovery; privacy-oriented architecture; NIME™; NHOS Oracle™; configuration-driven retrieval; FHIR R4; voice search; Web Speech API; internationalization; reproducible research; health informatics License Paper text: Creative Commons Attribution 4.0 International (CC BY 4.0)
Inc. NHOS Labs, Adedapo Ogundiran· Zenodo (CERN European Organi...· 0 citations
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