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Pharma Tech Outlook | Tuesday, July 14, 2020
CellNetix Pathology and Splintellx Inc. have collaborated to establish the SpIntellx HistoMapr-Breast Platform that uses explainable artificial intelligence (xAI) so that healthcare providers can efficiently and accurately diagnose and treat breast cancer.
FREMONT, CA: In the healthcare sector, artificial intelligence has become an essential technology because it is connected to various devices. To make use of the benefits of recent technologies in the healthcare industry, CellNetix Pathology and Splintellx Inc. have formed a partnership. The key reason for the collaboration of the companies is to authenticate the SpIntellx HistoMapr-Breast Platform.
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One of the growing pathology laboratory company is CellNetix Pathology & Laboratories, and they offer a wide range of subspecialty clinical and anatomic pathology services. Splintellx Inc. is a computational and systems pathology company that connects the computational power of the unbiased spatial analytics and explainable artificial intelligence (xAI) technologies. They provide their clients with proprietary software products and services to examine the pathology tissue sections.
This platform makes use of explainable artificial intelligence (xAI) so that healthcare providers can efficiently and accurately diagnose and treat breast cancer. This is the first platform to connect the power offered by xAI-assisted lab procedures while developing prognostics, diagnostics, and strategies. The influence of the platform can also be utilized while developing drugs for non-tumor and tumor diseases.
According to Dr. Dominique Coco, lead project pathologist with CellNetix Pathology & Laboratories, "we are thrilled to be working with SpIntellx in further developing and validating HistoMapr and the use of explainable artificial intelligence (xAI) in the practice of pathology." He further mentioned that "we see great potential in xAI which could rapidly reshape how we practice pathology."
In digital pathology, Splntellx has brought proprietary spatial analytics. This highly developed spatial analytics can capture the architecture and communication patterns of the various histological structures. Therefore, it helps to gain maximum information from the patients' tissue sections, and it can be used for clinical decisions and therapeutic strategies. Furthermore, the HistoMapr-Breast utilizes the data to offer accurate and unbiased justification to the automated recommendations. So, when the pathologists and other software ask questions to HistoMapr-Breasts, it can answer the primary issues by using the information while explaining its decision.
The technology can be a significant feature that can develop trust and transparency among the computational pathology systems and pathology disease experts. It is also a step that has been taken to adopt the AI connected digital pathology like deep learning. Moreover, with machine learning, there can be an immense improvement in communication among humans and machine learning tools.
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