BioIngine : Ingine Inc's Healthcare Data Science Venture
Machine Learning System Extracting Knowledge From Exhaustive (Millions of Records) and Uncertain System
Enabling Large Data Driven Evidence Based Medical Decision Support System
Ingine - BioEnterprise - Partnership
Together Solve Medical Computational Thinking, Learning and Reasoning
The™, a medical computational thinking, learning and reasoning platform for the Healthcare market. The BioIngine delivers Medical Automated Reasoning Programming Language Environment (MARPLE) capability based on the mathematics borrowed from several disciplines and notably from late Prof Paul A M Dirac's Quantum Mechanics (QM). Particularly the mathematical technique derived from QM and based on Dirac Notation for knowledge inference is called Hyperbolic Dirac Net (HDN).
Research and Innovation
The™ is a result of several years of efforts with Dr. Barry Robson; former Chief Scientific Officer, IBM Global Healthcare, Pharmaceutical and Life Sciences. His research has been in developing quantum math driven exchange and inference language achieving medical semantic interoperability, while also enabling Clinical Decision Support System based on the principles of Evidence Based Medicine (EBM) and its PICO (patient/problem/population-intervention-comparison-outcome) method.
BioEnterprise formed in 2002. Partner with people who have a passion for improving health and wellbeing. They are scientists, entrepreneurs, company founders with creativity and drive woven into their very DNA. Help them nurture innovative ideas and technologies from the embryonic stage, connecting them with critical resources and relationships, guiding them as they build their businesses, sell their products and services. We are experienced entrepreneurs and experts in rs grow their companies in Cleveland – The Medical Capital.
The BioIngine Algorithm - Ensemble of Mathematical Techniques
The HDN and Q-UEL are both based on the long used standard in quantum mechanics (QM) called Dirac Notation
Quantum Universal Exchange Language (Q-UEL) Is an algebraic notational language derived from the Dirac Notation, the mathematical machinery that defines quantum mechanics and a long and widely accepted standard in physics. Its concept endures as a powerful architectural principle, managing the problem of the interchange and merging of medical data and knowledge from a variety of formats and ontologies.
Zeta Theory
A combined information theory and number theory approach that can, first developed as a theory of expected information in bioinformatics that handles high dimensional problems and sparse data and can be combined with Dirac’s approach. The information measures readily convert to probabilities called zeta probabilities optionally including subjective prior probabilities that can be used in the HDN and other QUEL approaches. With ample data, the probabilities behave classically, with less, there is less information.
Hyperbolic Number
Dirac’s algebra also includes the hyperbolic imaginary number h, rediscovered by Dirac and described in various guises. It belongs to particle physics and did not appear in Schrödinger’s earlier wave mechanics. The purely h-complex algebra is the algebra required by the HDN and Q-UEL to give familiar descriptions about the everyday world when we are not interested in inference about waves.
Information Theory
The information theory aspects are explicit in the use of the partially summated Riemann zeta function as a measure of expected information in both sparse and extensive data. They are also implicit in the use of similarity and novelty or unusualness measures expected to be helpful in identifying anomalous records.
The BioIngine Capability - MARPLE
The Medical Automated Reasoning Programming Language Environment
Hyperbolic Dirac Net
Is a data science approach that employs breakthrough mathematical technique that brings the power of mathematical framework designed to describe Quantum Mechanics. The algorithmic technique is an ensemble of techniques borrowed from several disciplines and notably from late Prof Paul A M Dirac's Quantum Mechanics (QM). The mathematical framework derived from QM, is based on Dirac Notation for knowledge inference and is called Hyperbolic Dirac Net (HDN).
HDN as Hypothesis independent Unsupervised Machine Learning Approach
Employs unsupervised machine learning algorithmic approach based on Hyperbolic Dirac Net (HDN) that allows creation of inference nets that are a general graph (GC), including cyclic paths, thus surpassing the limitation in the Bayes Net that is traditionally a Directed Acyclic Graph (DAG) by definition. It is a long standing, peer reviewed, and well-proven concept. Basically HDN is an advanced version of Bayesian Inferential Statistics, and actually does make use of the famous Bayes equation while a traditional Bayes Net, paradoxically, does not.
HDN as Supervised Machine Learning approach
Employs supervised machine learning algorithmic that automatically builds HDNs composed of up to millions of tags, verifies the consistency of probabilities used, returns the estimate of probability value requested based on all those tags, and does pattern discovery to help explain the quantitative findings. Builds the largest possible inference net (HDN) based on odds (probability ratios) and does automatically with many automatic cross-checks and corrections.
HDN as a Semantic method Extracting and Learning from World Wide Web
Is a unsupervised unstructured web searching tool that employs Dirac Notation having strong relationship with the Semantic Structure used in the Semantic Web. The tool can quickly generate many millions of statements of knowledge. The extracted knowledge as semantic triples and semantic multiples are placed in the Knowledge Representation store.
The Bioingine - Probabilistic Thinking Reasoning and Learning System
Quantum Mechanics Machinery for Big Data Driven Medicine
Probabilistic Knowledge
The approach thus more fundamentally reflects the nature of probabilistic knowledge in the real world, which has the potential for taking account of the interaction between all things without limitation, and ironically this more explicitly makes use of Bayes rule far more than does a Bayes Net.
Deep Learning
It also allows more elaborate relationships than mere conditional dependencies, as a probabilistic semantics analogous to natural human language but with a more detailed sense of probability. To identify the things and their relationships that are important and provide the required probabilities, the scouts the large complex data of both structured and also information of unstructured textual character.
Suspends Cognitive Bias
It treats initial raw extracted knowledge rather in the manner of potentially erroneous or ambiguous prior knowledge, and validated and curated knowledge as posterior knowledge, and enables the refinement of knowledge extracted from authoritative scientific texts into an intuitive canonical “deep structure” mental-algebraic form that the can more readily manipulate.
The BioIngine Big Data Reasoning Platform While Solving Combinatorial Explosion
Ingine Inc is Washington DC based with office in Cleveland’s Global Center for Healthcare Innovation
The is Patent Pending IP belonging to Ingine; Inc™ - Ingine; Inc™, The™, DiracIngine™, MARPLE™ are all Ingine Inc © and Trademark Protected.