PALO ALTO, Calif., Aug. 02, 2018 (GLOBE NEWSWIRE) -- CloudMedx, a healthcare AI company that provides real time and actionable insights to the healthcare industry, today announced it is working with the Division of Gastroenterology at the University of California, San Francisco to help track progression of disease with patients identified with hepatocellular carcinoma (HCC) who are awaiting liver transplant, as well as predicting treatment outcomes. The goal is to provide tools to risk stratify patients, predict outcomes of certain care plans, and see which patients are at risk of dropping off the transplant wait list due to tumor progression or death. The goal will also be to match certain patients (donor to recipient) in an AI assisted manner which is data driven in order to automate and streamline this process.
Liver cancer, especially HCC, is one of the most dangerous forms of cancer. First of all, it is very hard to detect. It is typically detected at later stages when it already has metastasized and started to affect other organs in the body. The rate of progression of this disease is also very variable which makes treatment plans very arduous and time consuming. According to American Cancer Society, for the “43% of people who are diagnosed with Liver Cancer at an early stage, the 5-year survival rate is 31%. If liver cancer has spread to surrounding tissues or organs and/or the regional lymph nodes, the 5-year survival rate is 11%. If the cancer has spread to a distant part of the body, the 5-year survival rate is 3%”. With the help of CloudMedx’s AI Platform, the teams aim to automate and improve the process of hepatocellular carcinoma treatment early on and predict outcomes.
According to Neil Mehta, MD, assistant professor, and Bilal Hameed, MD, associate professor, in the UCSF Division of Gastroenterology, working with CloudMedx will provide them with insights into their own data and augment workflows, treatment options and planning. Most of this work is currently done manually and adds to administrative burden. Some of this heavy lifting may be done by a technology that can assist physicians in this decision-making process. CloudMedx provides its AI powered tools and services that are healthcare specific through its robust APIs that can integrate directly within physician workflows and can be customized to their specific requirements. The system also has the capability to learn from live data streams.
Currently, there is no individualized approach to patients with HCC who are placed on the liver transplant waitlist. However, it is clear that multiple factors such as severity of underlying liver disease (e.g., Child-Pugh or MELD score), response to local-regional treatments, tumor burden, and certain tumor markers affect an individual’s risk of waitlist dropout. Accurate, real-time dropout risk estimation along with improved matching of donors to recipients using AI tools to automate this process are critical steps in improving both the decision making of the multidisciplinary tumor board and transplant-related outcomes in HCC patients.
CloudMedx aims to reduce these manual tasks by reading through EMR and lab notes using its natural language processing tool and surfacing the insights so that care providers can act fast. The CloudMedx Platform analyzes both structured and unstructured data coming out of patient medical records such as electronic health records, labs, radiology reports and other data sources in order to highlight patient risks, outcomes, as well as assist in evidence-based guidelines and care plans to improve patient care and automate these processes.
About CloudMedx
CloudMedx is a "Clinical AI Platform" that provides real time clinical insights to the healthcare industry with the goal of improving clinical and financial outcomes. The company uses evidence based algorithms, machine learning and natural language to sift through both unstructured data as well as structured data to help providers and health systems to improve care delivery, reduce costs, and optimize their workflows.
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