Health Discovery Corporation (OTCBB: HDVY) is pleased to announce numerous additional issued patents and Notices of Allowance since its last press release describing its intellectual property portfolio. The Company now has a total of 37 issued patents, 4 Notices of Allowance and 30 pending patent applications.
New U.S. and Foreign Patents
The United States Patent and Trademark Office (USPTO) issued a patent to HDC that includes additional, broader claims to the Company’s exclusive Recursive Feature Elimination (RFE) using Support Vector Machines (“SVM”) or SVM-RFE method, the first patent for which issued in 2006. The SVM-RFE method has been used to successfully identify the most important pieces of information needed to solve complex pattern-recognition problems and has been shown in numerous peer-reviewed publications from some of the worlds top academic institutions to be a superior technology for the successful discovery of new molecular diagnostic/prognostic tests for personalized medicine. HDC has the only issued patents in the world for the SVM-RFE technology, which was discovered by members of the HDC science team. The SVM-RFE technology was the method used to discover the Company’s new tissue and urine based prostate cancer tests recently licensed to Quest Diagnostics (NYSE: DGX), Abbott Laboratories (NYSE: ABT) and Clarient Inc. (Nasdaq: CLRT).
The European Patent Office issued a notice of its intent to grant a patent covering HDC’s SVM-based computer-aided image analysis techniques. Corresponding patents have already been granted in the U.S., Australia and Japan. This is an important patent for the successful development of SVM based digital pathology and radiology interpretations. This significant patent protects HDC’s development of new tests for cervical cancer (PAP Smear Interpretation), circulating tumor cell (CTC) analysis in breast cancer and radiologic interpretation of mammograms for breast cancer.
Another newly issued USPTO patent covers an SVM-based data-mining platform for classification of data from heterogeneous biological datasets.