Deep Learning in Healthcare

Deep learning provides the healthcare industry with the ability to analyze data at exceptional speeds without compromising on accuracy. Deep learning uses mathematical models that are designed to operate a lot like the human brain. The multiple layers of network and technology allow for computing capability that’s unprecedented, and the ability to sift through vast quantities of data that would previously have been lost, forgotten or missed. These deep learning networks can solve complex problems and tease out strands of insight from reams of data that abound within the healthcare profession.

Mandatory practices such as Electronic Medical Records (EMR) have already primed healthcare systems for applying Big Data tools for next-generation data analytics. AI/ML tools are destined to add further value to this flow. They are expected to enhance the quality of automation and intelligent decision-making in primary/tertiary patient care and public healthcare systems. This could be the biggest impact of AI tools as it can potentially transform the quality of life for billions of people around the world.

Near-term opportunities

  • Image pathology
  • Drug discovery
  • Personalized medicine
  • Preventative care

Case Studies

EEG Diagnosis
Patent-pending Deep Learning technology developed to empower EEG diagnosis.
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Biomarker Discovery
Deep learning platform capable of detecting biomarkers of drugs and disease states.
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Bed Exit Detection
Convolutional LSTM models developed to detect overnight bed exits in hospital rooms.