Shastri Purushotma
See the following -
Artificial Intelligence Cluster Modeling on COVID-19 Data at Scale Offers Opportunity for Improved Patient Outcomes
Bitscopic Inc., a Silicon Valley based healthcare analytics company, has contracted with the VA Innovation Ecosystem 10X3 for a ground-breaking project to discover best practices in COVID treatment by examining large volumes of medical and other data sets from those who tested positive for COVID-19. The data includes patient health records, socio-economic data, epidemiological data for given geographic areas, and any available genomics or similar indicators for the discovery of significant patterns in patient subpopulations that can lead to improved care protocols and outcomes.
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Bitscopic's Machine Learning Algorithm Detects COVID-19 from Standard Blood Labs
Bitscopic Inc., a Silicon Valley based healthcare analytics company, announced today they have developed a machine learning prediction model that can identify COVID-19 infected patients using data from standard laboratory blood tests. The model, published in "Clinical Infectious Diseases," was developed using laboratory data from over 75,000 COVID-19 infected Veteran patients receiving care at VA medical centers. Payam Etminani, Bitscopic's CEO, said: "We are very excited by these results, as it demonstrates that inexpensive and easily attainable patient data can be used to construct a diagnostic fingerprint that can identify symptomatic cases of COVID-19. We are learning how the relatively blunt instrument of routine blood tests, through the power of machine learning, can be crafted into something approaching a precision tool."
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Shastri Purushotma
Shastri Purushotma is the Chief Content Officer at Bitscopic, a pioneering company in applying Artificial Intelligence to Medicine, as well as Chief Content Officer at B2B Buyer Insights, a research firm that is currently interviewing leaders in Finance on the Future of the Digital Economy. Read More »
Using Open Technology To Build a Biodefense Against the Coronavirus
As the number of US cases of the coronavirus rises, how will healthcare professionals be able to tell the difference between which panicked patients with similar symptoms has what? Even if the patient hasn't traveled to Wuhan or China recently, what if they sat at a Starbucks with someone who did? With the incubation time-lag before symptoms appear, who would even know? The challenge of monitoring 330 million people for infectious disease outbreaks is daunting. Take the flu as an example. During the last flu season which, as already discussed, was not as complex as this year's season, approximately 35.5 million Americans had flu symptoms, 16.5 million received medical care, 490,600 were hospitalized and 34,200 died.
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VA's Palo Alto Hospital Selects Bitscopic's PraediAlert Clinical Surveillance Platform
Bitscopic Inc., a Silicon Valley based healthcare analytics company, announced today that the US Department of Veteran's Affairs (VA) Palo Alto Medical Center has selected Bitscopic's PraediAlert platform for clinical surveillance. PraediAlert is an FDA registered clinical surveillance system that allows hospitals to improve patient care and patient safety by minimizing and managing patients at risk for hospital acquired infections (HAI) as well as optimizing care team productivity and workflows to improve patient outcomes.
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