Predictive Bioharmonics: A Universal Mathematical Model for Early Disease Prediction and Detection Across Biological, Physical, Thermal, Magnetic, Molecular and Quantum Systems
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| Format: | Recurso digital |
| Langue: | anglais |
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Zenodo
2025
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| _version_ | 1866901859104456704 |
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| author | Fries, Tess |
| author_facet | Fries, Tess |
| contents | <p dir="ltr">Predictive Bioharmonics proposes a universal, scale-invariant ratio model showing how disease can be predicted before its onset, across electrical, motion, video, thermal, magnetic, mechanical, blood-flow, molecular, and quantum domains. With the highest intent of predicting disease and ultimately eliminating it, I invite researchers worldwide to test and validate this model. </p> <p dir="ltr">Across all systems, the pre-disease state appears within 1.273–1.701, bounded by the Bioharmonic Threshold (√φ = 1.272), and although historically detected through diverse signals — from cfDNA drift and HRV instability to thermal hotspots, MEG/EEG fragmentation, ultrasound echo breakdown, and quantum decoherence — they all reflect the same mathematical transition. Predictive Bioharmonics provides the first unified table and AI-ready framework governed by φ, √φ, Fibonacci dynamics, and Feigenbaum scaling, proposing a possible mathematical signature associated with early disease and enabling detection long before conventional biomarkers. It describes the full life–death cycle with reversible and irreversible thresholds.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17764799 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Predictive Bioharmonics: A Universal Mathematical Model for Early Disease Prediction and Detection Across Biological, Physical, Thermal, Magnetic, Molecular and Quantum Systems Fries, Tess Predictive Bioharmonics Pre-Disease Detection Bioharmonic Threshold Scale-Ivariant Biology Multimodal Signals Universal Ratio Model Early Detection AI Health Prediction <p dir="ltr">Predictive Bioharmonics proposes a universal, scale-invariant ratio model showing how disease can be predicted before its onset, across electrical, motion, video, thermal, magnetic, mechanical, blood-flow, molecular, and quantum domains. With the highest intent of predicting disease and ultimately eliminating it, I invite researchers worldwide to test and validate this model. </p> <p dir="ltr">Across all systems, the pre-disease state appears within 1.273–1.701, bounded by the Bioharmonic Threshold (√φ = 1.272), and although historically detected through diverse signals — from cfDNA drift and HRV instability to thermal hotspots, MEG/EEG fragmentation, ultrasound echo breakdown, and quantum decoherence — they all reflect the same mathematical transition. Predictive Bioharmonics provides the first unified table and AI-ready framework governed by φ, √φ, Fibonacci dynamics, and Feigenbaum scaling, proposing a possible mathematical signature associated with early disease and enabling detection long before conventional biomarkers. It describes the full life–death cycle with reversible and irreversible thresholds.</p> |
| title | Predictive Bioharmonics: A Universal Mathematical Model for Early Disease Prediction and Detection Across Biological, Physical, Thermal, Magnetic, Molecular and Quantum Systems |
| topic | Predictive Bioharmonics Pre-Disease Detection Bioharmonic Threshold Scale-Ivariant Biology Multimodal Signals Universal Ratio Model Early Detection AI Health Prediction |
| url | https://doi.org/10.5281/zenodo.17764799 |