Data Science & AI

Data Science and Artificial Intelligence (AI) technology solutions are creating huge waves in industries across the globe, including healthcare. From patient care to diagnostic support, remote patient monitoring, virtual health assistants and others, the applications of ML & AI in healthcare are endless. 314e is helping healthcare organizations leverage the capabilities of ML & AI to eliminate routine and repetitive tasks to reduce waste and provide the best possible outcomes to their patients.

Machine Learning

Machine Learning & Artificial Intelligence for Healthcare

314e’s Business Intelligence practice utilizes machine learning competencies and practices, coupled with robotic process automation (RPA), using AI-Adapt technology-enabled data services to provide data enrichment/extraction services and solutions aimed at improving patient care and reducing cost.

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Use Case Development

Get help to take you from ideation through documentation of relevant Data Science use cases

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Data Analytics

Process large data sets to create complex visualizations

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Powerful Data Models

Build powerful data models on top of data warehouses using the best tool sets

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Natural Language Processing (NLP)

Build NLP techniques to power more human-relevant interactions

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Machine Learning

Build and deploy a machine learning platform to scale through and process enormous data sets

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Robotic Process Automation (RPA)

Streamline processes and improve operations while working on large data sets

Healthcare Data Science Use Cases

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Wearable Technology Integration with EMR to Improve Patient Care

With the advancement of wearable technology, physicians are deeply interested in understanding patient behavior and the practice of self patient care in the treatment of chronic medical conditions. Wearable devices provide clinicians with access to more pertinent information to improve treatment methods, save cost and guarantee positive health outcomes.

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Disease Diagnostics and Early Disease Prevention

Through the application of deep learning and big data processing techniques, practices can analyze big data to detect early symptoms of chronic diseases and better care or patients, in turn, managing the patient population needs of the community they serve.

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Population Health Management

Patient healthcare data is scattered across various sources which include wearables, social media, social determinants of health (SDOH) and others. Effective population health management involves data analysis related to patient geography, health ailments and more.

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Cost Savings

Healthcare practices can leverage the analysis of data using best-practice driven data sciences to manage operations to keep healthcare costs to the minimum. Using the power of big data analytics, it is possible to optimize the use of healthcare resources, guarantee positive patient outcomes and minimize unnecessary hospital readmissions

Machine Learning (ML) and Artificial Intelligence (AI) Technology Expertise

  • Data Analytics:
    For processing big data streams (Apache Spark, Apache Apex)
  • Machine Learning / Deep Learning:
     Building powerful data models on top of big data (Apache MXNet, Keras/TensorFlow, Azure ML, PyTorch)
  • Natural Language Processing (NLP):
     Building NLP to power more human-relevant interactions (NLTK, Stanford NLP, spaCy)
  • Robotic Process Automation (RPA):
     UiPath, Eggplant, taskt

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