How much are machine learning and NMR related in medical imaging?

In summary, the conversation discusses the correlation between machine learning and medical imaging, specifically in the field of medicine and medical imaging. The use of machine learning in computer-assisted diagnosis and other tasks in medical imaging is a big area of research, with potential for improvement. The positions in this field are mainly for individuals with a PhD.
  • #1
Domenico94
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Hi everyone. By reading stuff on the Internet, I found many times the correlation between machine learning and NMR, or, better, algorithms that are implemented for that kind of technology( The same goes for PET, or CT scans.
The thing I want to ask is, how much do you think that the two things are related? You think that machine learning is used a lot in that kind of research, or is it still a thing that it's somehow neglected in that field? I'm talking esclusively of medicine and medical imaging, not in general.
 
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  • #2
You might want to search for "computer assisted diagnosis" to get an idea of the state of the field. In general, this is a big area of research in medical imaging. Even basic tasks like atlas-based anatomical segmentation and delineation are just over the past few years coming out in commercial products, and even then there's a lot of debate over how reliable such systems are. So there is definitely a lot of room for improvement, if these are areas you're interested in.
 
  • #3
Choppy said:
You might want to search for "computer assisted diagnosis" to get an idea of the state of the field. In general, this is a big area of research in medical imaging. Even basic tasks like atlas-based anatomical segmentation and delineation are just over the past few years coming out in commercial products, and even then there's a lot of debate over how reliable such systems are. So there is definitely a lot of room for improvement, if these are areas you're interested in.
Actually I ve read of it...but I just didn't know how much that sector was developed..Now it seems more clear, thanks :)
You know if their positions for those jobs are for people with master s degree or only for PhD people? I mean, developing medical imaging stuff for that kind of machiner..Like MRI and so on...
 
  • #4
I think most of the people actively doing research in such areas are at the PhD level.
 
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Likes Domenico94
  • #5
Choppy said:
I think most of the people actively doing research in such areas are at the PhD level.
Understood:) thanks: P
 

What is machine learning?

Machine learning is a branch of artificial intelligence that involves teaching machines to learn from data and make predictions or decisions without being explicitly programmed. It uses algorithms and statistical models to find patterns and make decisions based on those patterns.

What is NMR?

NMR stands for nuclear magnetic resonance, which is a technique used to study the physical and chemical properties of molecules. It involves applying a magnetic field to a sample and observing how the nuclei of atoms in the sample respond, providing information about the structure and behavior of the molecules.

How can machine learning be applied to NMR?

Machine learning can be applied to NMR data to help analyze and interpret the large amounts of data produced by NMR experiments. It can be used to identify patterns and correlations in the data, classify different types of molecules, and make predictions about the properties of molecules based on their NMR spectra.

What are the benefits of using machine learning for NMR analysis?

Using machine learning for NMR analysis can save time and resources by automating the data analysis process. It can also provide more accurate and consistent results by eliminating human error and bias. Additionally, machine learning can help identify subtle patterns in the data that may be missed by manual analysis.

Are there any limitations to using machine learning for NMR analysis?

One limitation of using machine learning for NMR analysis is that it requires a large amount of high-quality data to train the algorithms. Additionally, the accuracy of the results is highly dependent on the quality of the data and the chosen algorithm. It is also important to have a good understanding of both machine learning techniques and NMR principles in order to properly interpret the results.

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