How Machine Learning Will Transform Biomedical Research - PowerPoint PPT Presentation

About This Presentation
Title:

How Machine Learning Will Transform Biomedical Research

Description:

Thanks to engineering applications, machine learning is making it possible to model data extremely well, without using strong assumptions about the modeled system. Machine learning can usually better describe data than biomedical models and thus provides both engineering solutions and an essential benchmark. – PowerPoint PPT presentation

Number of Views:249

less

Transcript and Presenter's Notes

Title: How Machine Learning Will Transform Biomedical Research


1
  • Session 1

2
  • Technological advancements have made our world
    different in a good sense. It has impacted
    different areas of our life, even the medicine,
    and pharma sector. We are now living in an era
    where technology is influencing the way medical
    facilities and medicines are administered to
    people. All this requires a lot of research and
    development. Machine learning is playing a key
    role in this. Today machine learning experts are
    using their skills to make some outstanding
    developments in the field of biomedical research,
    and we will be exploring the same in this blog.
  • As per the reports of McKinsey, big data and
    machine learning generate a value of up to 100
    billion in the field of pharma and medicine. This
    is based on enhanced decision making, improving
    the efficiency of research and clinical trials,
    and creating new tools. In the pharma and medical
    field, the burgeoning applications of machine
    learning in the pharma and biomedical sciences
    show the glimmering scope of ML.

3
Here Is How Machine Learning Is Impacting
Biomedical Research
  • Identification Of Disease- one of the biggest
    uses of machine learning is identifying diseases.
    As per the report of Pharmaceutical Research and
    Manufacturers of America (2015), more than 800
    medicine and vaccines are in trial. These
    medicines are used for treating cancer. Many
    large pharma companies are making use of machine
    learning methodologies that are eventually
    enhancing the work process. Since this technology
    focuses on better assessment of data and finding
    out a solution. IBM Watson Health announced IBM
    Watson Genomics that aims to make developments in
    making medicines more effective by integrating
    cognitive computing and genomic tumor sequencing.

4
  • Personalized Treatment- Another area of
    application of ML is in administering
    personalized treatment. This medicine is
    developed by administering the personal health of
    an individual. Personalized medicine is a more
    effective treatment based on individual data
    paired with predictive analytics. This will help
    in better assessment of disease. IBM Watson
    Oncology is a leading name working in this domain
    and is making use of a patient's personal
    information and history to optimize the treatment
    option. Although this research is at the initial
    stage, it holds a lot of prospects in the future.
    With the use of data about patients, it will be
    easier for medical practitioners to render the
    right kind of medicine to individuals.

5
  • Drug Discovery- The use of machine learning in
    drug discovery is at the nascent stage. But, it
    surely has the potential to make some significant
    changes, starting from the initial screening of
    drugs to predict the success rate of medicine
    based on the patient's personal medical
    information. It used RD technologies like
    next-generation sequencing. Another point that we
    would like to mention here is precision medicine,
    which involves identifying medicines for diseases
    and finding alternative therapy paths. Much of
    this involves unsupervised learning.

6
  • Clinical Trial Research- ML has a lot of
    potential to shape and direct clinical trial
    research. Using predictive analytics to identify
    candidates for clinical trials can draw a much
    wider range of data than the technologies we are
    using today. This information includes genetic
    information, doctor's visit, etc.
  • Besides, ML can also be used for monitoring, and
    real-time data access to enhance safety. For
    example, screening the biological and other
    signals of harm.
  • As per the report of McKinsey, many ML
    applications will help in increasing clinical
    trial efficiency, like finding the best sample
    size to enhance the efficiency of medical
    procedures.

7
  • These are just a few of the many use cases of
    machine learning in the field of pharma and
    biomedical research. Various developments are
    going on in this field.
  • Many companies are now employing machine learning
    experts or looking for individuals who have
    machine learning certification. Machine learning
    uses a wide range of algorithms and
    methodologies, which can eventually enhance
    medical research.

8
What's Next?
  • Owing to huge development and demand in ML, it
    has emerged as a popular career option. Nowadays,
    many individuals are seeking this as a career
    option. Global Tech Council is providing an
    online machine learning certification program.
    This machine learning training incorporated
    complete learning about machine learning and
    allowed concepts. You will also learn about the
    information and the role of AI in healthcare.
    Both these are going to increase in the times to
    come. If you are also willing to become a machine
    learning expert, you must go for a machine
    learning certification program.

9
Conclusion
  • Machine learning is a game-changer in the field
    of technology. It is paving the way for a lot of
    development, which is eventually going to benefit
    the pharma and medical field. Leveraging ML in
    pharma and medical has become a prime interest
    for many big names in the industry. ML has
    triggered the medical revolution by improving it
    and making it more efficient and flawless.

10
(No Transcript)
Write a Comment
User Comments (0)
About PowerShow.com