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Optimization for Healthcare Insurance companies
Insurers are using artificial intelligence and machine learning to review medical records, optimize care for chronic conditions, identify risk.
ML algorithms detect patterns associated with diseases and health conditions by studying thousands of healthcare records and other patient data.
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Artificial intelligence can support radiologists and pathologists as they use medical imaging to diagnose a wide variety of conditions.
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ML can use real-time data, information to improve the accuracy of surgical robotic tools. The benefits include reduced human error, aid during more complex procedures and less invasive surgeries.
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Optimized for speed, accuracy, and scalability. Best Practices and is fully configurable, allowing users to choose which steps, parameter settings, and versions of the pipeline to run.
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Brings intelligent video analytics and conversational AI capabilities to healthcare, simplifying the development for automated body temperature screening, protective mask detection, and remote patient monitoring.
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To meet the growing demand for care, medical technology leaders are turning to AI tools that can help radiation oncologists provide high-quality, individualized treatment faster.
Adverse drug reactions (ADRs) are an important concern in the medication process and can pose a substantial economic burden for patients and hospitals. Because of the limitations of clinical trials, it is difficult to identify all possible ADRs of a drug before it is marketed. We developed a new model based on data mining technology to predict potential ADRs based on available drug data.
Showcase of awesome works we have done for our clients
Insurers are using artificial intelligence and machine learning to review medical records, optimize care for chronic conditions, identify risk.
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