From Seeking Alpha
Health Discovery Corp.: Synthesizing Machine Learning And Medicine
Sep. 01, 2021 1:02 PM ETHealth Discovery Corporation (HDVY)1 Comment
Summary
Health Discovery Corp. Support Vector Machines (SVM) marked a breakthrough in the theory of learning systems outperforming neural networks.
SVMs are able to process infinite amounts of data and analyze data to find separations and delineations within high dimensionality.
The Company identified a new technique in SVMs - Recursive Feature Elimination (SVM-RFE), for which they hold the only issued patents.
Looking for more investing ideas like this one? Get them exclusively at The Total Pharma Tracker. Learn More »
CPU and Computer chip concept Central Computer Processor 3D rendering
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About
Source: company website
Health Discovery Corporation (OTCPK:HDVY) is a machine learning (ML) company using advanced mathematical techniques to analyze large amounts of data to recognize patterns primarily in the field of molecular diagnostics, which has enormous potential for scientific discovery. The Company synthesizes ML and medicine to develop more personalized approaches to the diagnosis and treatment of certain diseases. Recognizing patterns is the hallmark of artificial intelligence (AI) derived algorithmically from the complex mathematical and statistical analysis of voluminous data. This AI is useful not only in medical discovery but also in healthcare technology, finance and other high-tech markets.
The technology
The Company made several discoveries in the medical diagnostics field and evolved the technology called Support Vector Machines (SVM) based on statistical learning theory (SLT), which provides a new modeling framework for learning algorithms, merging ML and statistics to derive AI. The SVMs have the ability to process and analyze infinite amounts of data within high dimensionality, outperforming neural networks that are advanced statistical modeling methodologies, but have limited ability to analyze data, that too from two or three dimensions only. Applying SVM techniques to complex genetic and proteomic data, the Company discovered biomarkers that form the basis of its intellectual property protected by 21 patents issued or pending around the world, with expirations ranging from 2022 to 2033.
The Company's experts also identified a technique to filter tissue-specific genes from those related to malignancy, and also identify gene patterns expressing the severity of a disease. This technique called the Support Vector Machine-Recursive Feature Elimination (SVM-RFE) can be used to "discriminate relationships within clinical datasets" such as distinguishing normal versus abnormal tissues. SVM-RFE "is an enhanced decision-making tool for pharmacogenic and toxicological profiling" of a patient, allowing the development of truly personalized therapies. The SVM-RFE technique can not only find genes implicated in a disease but also rank the analyzed genetic information to determine and identify the important genes in the molecular diagnostic test, as well as identify patentable IP-free genes. Health Discovery Corp. holds the only issued patents in the world for the SVM-RFE technology, confirmed in the Company's favor by the U.S. Patent and Trademark Office (USPTO) subsequent to an interference proceeding between the Company and Intel Corporation. Furthermore, the USPTO granted a Patent Term Adjustment (PTA) extending the patent term up to June 7, 2025.
The Company initially used the SVMs internally to discover and license biomarker signatures. Currently, its commercialization efforts include utilization of the IP and its expertise to help develop diagnostic and prognostic predictive tests, to license SVM technologies directly to diagnostic companies, and, to potentially form new ventures with domain experts in other fields where its pattern recognition technology has commercial value.
The SVMs are one of the leading approaches to pattern recognition and machine learning exceedingly popular worldwide, and are replacing neural networks and other methodologies in a variety of fields including bioinformatics, engineering, and information retrieval, for several applications, including "image analysis, text and image classification, handwriting and speech recognition, fingerprint identification, face recognition, fraud detection, financial securities prediction, protein structure prediction, medical diagnosis and prognosis, classification of microarray gene expression data, identifying consumer purchasing patterns, weather prediction, decryption, vehicle control monitoring, prediction of traffic variables in transportation systems, and many others."
Financials
As of 6/30/2021, the Company's accumulated deficit was $32.195 million. Cash balance was $0.485 million. Debt was 0.212 million. Operating expenses for 1H-2021 were $2.048 million. The Company estimates a cash run until 1Q-2022 and plans to raise funds for continuing operations by licensing the Company patents, pursuing infringement opportunities and obtaining additional equity or debt financing.
The Company's market capitalization as of 8/30/2021 was $72.79 million on a stock price of $0.21 with 404.38 million shares outstanding, of which the public holds 70.67% and insiders hold 29.20%.
Risks
Although the Company has been granted favorable decisions and motions in multiple petitions brought against it by Intel Corporation, an Inter Partes Review (IPR) of the Company's SVM-RFE, filed by Intel in February 2021 with the USPTO, remains pending after response by the Company. (Ref.: 10-Q, page 16).
Between February 2020 and April 2021, multiple abusive litigations were brought upon the Company by two shareholders, which were all dismissed, however, a similar litigation by another shareholder filed in September 2020 with virtually identical claims as those of the earlier abusive litigations, remains pending, and is now in the discovery phase. (Ref.: 10-Q, page 17).
Bottom line
The next two quarters are critical for the Company to raise further financing, whether via licensing of its IP or via equity, and to overcome the pending litigations. We will avoid the Company for now.
Health Discovery Corp.: Synthesizing Machine Learning And Medicine
Sep. 01, 2021 1:02 PM ETHealth Discovery Corporation (HDVY)1 Comment
Summary
Health Discovery Corp. Support Vector Machines (SVM) marked a breakthrough in the theory of learning systems outperforming neural networks.
SVMs are able to process infinite amounts of data and analyze data to find separations and delineations within high dimensionality.
The Company identified a new technique in SVMs - Recursive Feature Elimination (SVM-RFE), for which they hold the only issued patents.
Looking for more investing ideas like this one? Get them exclusively at The Total Pharma Tracker. Learn More »
CPU and Computer chip concept Central Computer Processor 3D rendering
Olemedia/E+ via Getty Images
About
Source: company website
Health Discovery Corporation (OTCPK:HDVY) is a machine learning (ML) company using advanced mathematical techniques to analyze large amounts of data to recognize patterns primarily in the field of molecular diagnostics, which has enormous potential for scientific discovery. The Company synthesizes ML and medicine to develop more personalized approaches to the diagnosis and treatment of certain diseases. Recognizing patterns is the hallmark of artificial intelligence (AI) derived algorithmically from the complex mathematical and statistical analysis of voluminous data. This AI is useful not only in medical discovery but also in healthcare technology, finance and other high-tech markets.
The technology
The Company made several discoveries in the medical diagnostics field and evolved the technology called Support Vector Machines (SVM) based on statistical learning theory (SLT), which provides a new modeling framework for learning algorithms, merging ML and statistics to derive AI. The SVMs have the ability to process and analyze infinite amounts of data within high dimensionality, outperforming neural networks that are advanced statistical modeling methodologies, but have limited ability to analyze data, that too from two or three dimensions only. Applying SVM techniques to complex genetic and proteomic data, the Company discovered biomarkers that form the basis of its intellectual property protected by 21 patents issued or pending around the world, with expirations ranging from 2022 to 2033.
The Company's experts also identified a technique to filter tissue-specific genes from those related to malignancy, and also identify gene patterns expressing the severity of a disease. This technique called the Support Vector Machine-Recursive Feature Elimination (SVM-RFE) can be used to "discriminate relationships within clinical datasets" such as distinguishing normal versus abnormal tissues. SVM-RFE "is an enhanced decision-making tool for pharmacogenic and toxicological profiling" of a patient, allowing the development of truly personalized therapies. The SVM-RFE technique can not only find genes implicated in a disease but also rank the analyzed genetic information to determine and identify the important genes in the molecular diagnostic test, as well as identify patentable IP-free genes. Health Discovery Corp. holds the only issued patents in the world for the SVM-RFE technology, confirmed in the Company's favor by the U.S. Patent and Trademark Office (USPTO) subsequent to an interference proceeding between the Company and Intel Corporation. Furthermore, the USPTO granted a Patent Term Adjustment (PTA) extending the patent term up to June 7, 2025.
The Company initially used the SVMs internally to discover and license biomarker signatures. Currently, its commercialization efforts include utilization of the IP and its expertise to help develop diagnostic and prognostic predictive tests, to license SVM technologies directly to diagnostic companies, and, to potentially form new ventures with domain experts in other fields where its pattern recognition technology has commercial value.
The SVMs are one of the leading approaches to pattern recognition and machine learning exceedingly popular worldwide, and are replacing neural networks and other methodologies in a variety of fields including bioinformatics, engineering, and information retrieval, for several applications, including "image analysis, text and image classification, handwriting and speech recognition, fingerprint identification, face recognition, fraud detection, financial securities prediction, protein structure prediction, medical diagnosis and prognosis, classification of microarray gene expression data, identifying consumer purchasing patterns, weather prediction, decryption, vehicle control monitoring, prediction of traffic variables in transportation systems, and many others."
Financials
As of 6/30/2021, the Company's accumulated deficit was $32.195 million. Cash balance was $0.485 million. Debt was 0.212 million. Operating expenses for 1H-2021 were $2.048 million. The Company estimates a cash run until 1Q-2022 and plans to raise funds for continuing operations by licensing the Company patents, pursuing infringement opportunities and obtaining additional equity or debt financing.
The Company's market capitalization as of 8/30/2021 was $72.79 million on a stock price of $0.21 with 404.38 million shares outstanding, of which the public holds 70.67% and insiders hold 29.20%.
Risks
Although the Company has been granted favorable decisions and motions in multiple petitions brought against it by Intel Corporation, an Inter Partes Review (IPR) of the Company's SVM-RFE, filed by Intel in February 2021 with the USPTO, remains pending after response by the Company. (Ref.: 10-Q, page 16).
Between February 2020 and April 2021, multiple abusive litigations were brought upon the Company by two shareholders, which were all dismissed, however, a similar litigation by another shareholder filed in September 2020 with virtually identical claims as those of the earlier abusive litigations, remains pending, and is now in the discovery phase. (Ref.: 10-Q, page 17).
Bottom line
The next two quarters are critical for the Company to raise further financing, whether via licensing of its IP or via equity, and to overcome the pending litigations. We will avoid the Company for now.
