Healthcare industry across the world has progressed very rapidly over the last two decades. However, the healthcare industry is behind other sectors in adopting the newer IT technologies. This talk primarily focuses on imbibing Artificial Intelligence (AI) in medical domain innovations. Like other revolutionary advances in medicine, AI is to be integrated into healthcare practices.

Healthcare using Artificial Intelligence is amongst the fastest growing research area across the globe. A massive amount of heterogeneous data generated in healthcare sector offers opportunities for big data analytics. Such analysis transforms big data into real and actionable insights to healthcare practices, thus provide new understanding and ways for better and quicker treatment and improve overall individual and population health.

Recent advancements in AI are proving beneficial in development of applications in various spheres of healthcare such as microbiological analysis, discovery of drug, disease diagnosis, Genomics, medical imaging and bioinformatics. Due to increasing availability of electronic healthcare data (structured as well as unstructured data) and rapid progress of analytics techniques, a lot of research is being carried out in this area. Popular AI techniques include machine learning/deep learning for structured data and natural language processing for unstructured data. Guided by relevant clinical questions, automation using AI can unlock clinically relevant information hidden in the massive amount of structured/unstructured data, which in turn can assist clinical decision making.

The talk connects three contemporary areas of research: AI, Healthcare and Bigdata Analytics. It will provide attendees a collective update on developments in healthcare using AI, major challenges, opportunities and future research directions.

 
 

Outline/Structure of the Talk

  • Emergence of AI in Healthcare (2 mins)
  • Application Areas of AI in Healthcare (3 mins)
  • Discussion of AI-Powered Healthcare Applications (7.5 mins)
    • AI-based Drug Design and Development
    • DL-based Craniofacial Distance Measurement for Facial Reconstructive Surgery
    • Prediction of Next Action in Minimally Invasive Surgery
  • Significance of Explainable AI (XAI) for Healthcare (3 mins)
  • Challenges and Future Opportunities (2.5 mins)
  • Q & A (2 mins)

Learning Outcome

After attending this session, the attendees will ...

  • understand how AI can be utilized in healthcare sector to make faster, cheaper, reliable and accurate decisions.
  • be familiar with application areas of AI in healthcare and future research opportunities in healthcare sector.

Target Audience

Data Scientists, Machine Learning/Deep Learning Practitioners, Industry Professionals from Healthcare Sector, Researchers, Doctors, Students & Faculty Members from Engineering and Technology as well as Medical.

Prerequisites for Attendees

Basic understanding of neural networks.

schedule Submitted 3 months ago

Public Feedback

comment Suggest improvements to the Speaker
  • Natasha Rodrigues
    By Natasha Rodrigues  ~  3 months ago
    reply Reply

    Hi Dr. Mayuri,

    Thanks for your proposal! To help the program committee understand your proposal a little better, can you add the slides for your proposal.

    Also, in order to ensure the completeness of your proposal, we suggest you go through the review process requirements

    Thanks,

    Natasha

    • Dr. Mayuri Mehta
      By Dr. Mayuri Mehta  ~  3 months ago
      reply Reply

      Thank you Natasha for your feedback. As required I have uploaded a FEW SAMPLE SLIDES of my presentation for reference.

      Review process requirements are available either in the proposal itself or in my profile. However, if I have missed out something, request you to kindly inform me.

      Thank you.

      • Natasha Rodrigues
        By Natasha Rodrigues  ~  3 months ago
        reply Reply

        Thanks Dr. Mayuri for your response. We are just making sure that the Program Committee has all the necessary information to review the proposal. We will let you know if we need more details.


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