Healthcare / Pharma
Healthcare and Pharmaceutical companies have vast amounts of data full of untapped potential. This data can be leveraged for problems ranging from Prescription and Claims fraud to Multi-Channel promotional outreach across multiple brand portfolios.
AI FOR HEALTHCARE AND PHARMACEUTICAL
Machine learning and AI have transformed the healthcare and pharmaceutical industry. State-of-the-art machine learning technologies and algorithms are helping companies fight prescription fraud, personalize outreach, research the next wave of therapeutics, predicting ICU transfers, drug discovery along with many other applications.
Claims Fraud Detection
AI is ideally suited to fraud detection for medical claims. Machine learning models can be used to automate claims assessment and routing based on existing fraud patterns. This process flags potentially fraudulent claims for further review, but also has the added benefit of automatically identifying good transactions and streamlining their approval and payment.
Predicting Hospital Re-admissions
Using AI driven models, providers can predict which patients are most likely to develop central-line infections by looking and a variety of data including patient information, treatment history and staff history. With this prediction, clinicians can monitor high-risk patients and intervene to reduce risk.
Claims Denial Management
Machine learning models can be used to streamline the denials management process by finding claims that have a high likelihood of being paid and the highest potential value. By working these claims first, the providers and payers spend the time on those claims that are most likely to be valid and will yield the most value to patients and providers.
We bring extensive cross-industry expertise to design, build, and deploy custom machine learning solutions.
Leverage advanced computer vision to build applications that make sense of the world by identifying, segmenting, and tracking objects.
Use state of the art deep learning models and machine vision for classification, recognition, tracking, and detection.
Development and Data Architecture
Rapidly build and embed machine learning pipelines in software and web applications.
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