AI in Healthcare

Artificial Intelligence in Telemedicine

Artificial Intelligence in Medical Diagnosis

  • MRI scans are very difficult to analyze due to the amount of information they contain. A normal MRI scan analysis takes several hours, and researchers are trying to formulate an outcome from large data sets, wait for hours for a computer to regenerate the scans.
  • Large and complex data sets can be analyzed with the help of neural networks and this is exactly what a team of researchers implemented at MIT. They developed a neural network which they called “VoxelMorph” that was trained on a data set of approximately 8000 MRI scans.
  • A neural network functions by inputting data at one of the ends which undergoes a transformation throughout the network until the final desired output is achieved. A neural network works on the principle of weights and bias.

Artificial Intelligence in Drug Discovery

Artificial Intelligence in Medical Assistance

  • Self-care
  • Nurse Line
  • Clinical advice
  • Scheduling an appointment
  • ER Direction

Artificial Intelligence in Decision Making

  • Aiding and helping surgeons with an advanced set of instruments.
  • Translating and converting the surgeon’s hand movements at the console in real-time.
  • Producing 3D high-definition, clear, and magnified image of the surgical area.

Knowing the current limitations of AI in healthcare

Summary

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Artificial Intelligence in Healthcare

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Tejas Kachare

Tejas Kachare

Artificial Intelligence in Healthcare

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