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Smart Health Care

Author

Listed:
  • Sujitha M
  • Jinu P Sainudeen
  • Nimmymol Manuel
  • Neena Joseph

Abstract

Data is the lifeblood of all business. Data-driven decisions increasingly make the difference between keeping up with competition or falling further behind. Machine learning can be the key to unlocking the value of corporate and customer data and enacting decisions that keep a company ahead of the competition. A subset of artificial intelligence (AI), machine learning (ML) is the area of computational science that focuses on analyzing and interpreting patterns and structures in data to enable learning, reasoning, and decision making outside of human interaction. Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyze and make data-driven recommendations and decisions based on only the input data. If any corrections are identified, the algorithm can incorporate that information to improve its future decision making. Machine learning helps in data-driven decision making, identification of key trends and driving research efficiency. When it comes to healthcare, there are different ways in which machine learning techniques can be applied for effective diseases prediction, diagnosis, and treatments, improving the overall operations of healthcare. Effective machine learning implementation enables healthcare professionals in better decision-making, identifying trends and innovations, and improving the efficiency of research and clinical trials.

Suggested Citation

  • Sujitha M & Jinu P Sainudeen & Nimmymol Manuel & Neena Joseph, 2018. "Smart Health Care," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 3(6), pages 702-706, August.
  • Handle: RePEc:jbh:ijsrcs:v3:y2018:i6:id:hcseit2172423
    Note: Article URL: https://ijsrcseit.com/CSEIT2172423
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