Ibex Health Data Systems is a leading provider of information technology for the healthcare industry. In September 1999, Dr. Sullivan installed the Ibex system in his emergency department. In a joint venture, Ibex and The Sullivan Group put their risk management system on-line, creating a product called RiskCheck(r).
Ibex Second Read(tm) Application Detects Isolated major Errors in Retrospective PCNBs
The Ibex Second Read(tm) system uses advanced machine learning techniques to analyze the resulting pathology reports. The application was trained on the Maccabi Institute’s pathology data, the world’s first AI powered cancer diagnostic lab. Now, pathology labs around the world use the system to improve their diagnostic accuracy by reducing the number of missed cancer cases.
A startup in Israel, Ibex Medical Analytics, is deploying its AI-powered cancer diagnostic system at a leading pathology institute in Israel. Its technology identifies major errors in retrospective PCNBs. The company claims the system has the potential to reduce cancer-related errors by up to 40%. The company is already piloting the system at Maccabi Healthcare Services, Israel’s largest healthcare provider. The AI-based Second Read system has already successfully identified a majority of erroneous diagnoses among retrospective PCNBs.
With the use of artificial intelligence, Inspirata and Ibex customers can further reduce their errors and increase operational efficiency. The Ibex Second Read application is fully integrated with Inspirata’s digital pathology solution, helping physicians identify cancerous tissue and notify them when a discrepancy is identified. Because the technology is integrated with the Inspirata solution, its users can benefit from full access to all capabilities within a single platform.
Ibex health data systems algorithms are powerful and effective in analyzing image data. Using image data import, users can create ROIs and image pairs in Ibex. They can also double-check their algorithms by reviewing intermediate data. The data workspace includes tools for anonymizing ROI data and image pairs. Here are the features of Ibex’s health data systems algorithms. You can choose from the following scenarios:
The ibex developer studio allows for the integration of additional algorithms. ibex supports the MVC concept, which helps maintain data consistency and reproducibility between different systems. Users can also define their own algorithms using the developer studio. The ibex health data systems algorithm library includes components like workspace, image preprocessing and feature extraction algorithms, and predictive model formula. Each component can be exported and imported to create models.
Another example of Ibex’s health data systems algorithms is its use in pathology. This company developed algorithms to help pathologists analyze images of biopsy samples. The algorithms help pathologists to identify cancerous tissue, grade cancer, and recognize clinically significant features. These algorithms have significantly reduced error rates and improved average time for a particular case. Currently, these algorithms are used in prostate biopsies, but they are expected to be used in more medical procedures as well.
Ibex also supports the quality assurance of data and feature algorithms. Users can validate the results of their feature algorithms by manually checking their inputs. In addition, ibex supports the sharing of model and data files. This makes the model reproducible in different institutions. Further, ibex has an integrated workflow. By integrating the health data systems algorithms, researchers can create a reproducible model of patient data.
Ibex Medical Analytics, an Israeli company that has more than 400 locations, and Hartford HealthCare, which serves more than 17,000 people each day, have announced a clinical research collaboration to develop an artificial intelligence solution. Ibex’s Galen breast diagnostic algorithm has received CE mark certification, and its technology is available to pathologists across Europe. Its AI solutions are highly reliable and can improve patient outcomes.
Ibex health data systems algorithms use IBEX synthetic data that far outperforms AI trained on real data. IBEX synthetic data covers every imaginable system configuration, protocol, and patient type. It speeds up AI development and validates AI before spending money on expensive clinical data. With the Trueview X-ray simulator, users can rapidly develop new product concepts and validate the commercial business case without investing in expensive clinical trials. They can also assess the effect of post-processing on AI accuracy.
Inspirata’s Dynamyx Architecture
Inspirata is a provider of cancer informatics and digital pathology solutions. The SUNY Upstate Health System has gone live with Inspirata’s Dynamyx architecture for digital pathology. The goal of the new system is to integrate pathology systems across the enterprise and present clinical data to physicians in more efficient ways, while minimizing daily burdens. The company will highlight its technical partnerships at the Pathology Informatics Summit 2019.
Developed in partnership with industry leaders, Patholytix Preclinical incorporates AI software to streamline diagnosis. It is the first vendor-agnostic solution for digital pathology, enabling seamless integration with a variety of scanners. Its advanced workflow management tools, image evaluation, and case management tools combine with AI solutions to reduce error rates and improve patient care.
The Dynamyx architecture is cloud-based and designed for integration with other systems. The company’s partnership with OptraSCAN ensures seamless integration with WSI scanners. It supports up to 480 slides and is equipped for confocal, brightfield, and fluorescence imaging. It is CE-marked as an imaging system for diagnostic procedures, but is not intended for invasive diagnostic procedures.
Inspirata has created a unique solution to address this challenge. The company has developed an artificial intelligence-based application called Ibex Second Read that allows doctors to use a machine learning algorithm to analyze cancer images. Its partners have a combined track record of development and success in medical imaging. Inspirerata has a team of experts dedicated to digital pathology and AI.
The ibex health data systems Second Read application uses artificial intelligence to analyze biopsy images and identify cancerous tissue. The algorithms identify cancerous tissue and alert physicians in the case of a discrepancy. With the integration of the two technologies, customers benefit from full access to all the capabilities of both systems on a single platform. The new solution will be available as early as this year.
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