How can computer science be applied to the medical field

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Discussion Overview

The discussion explores the intersection of computer science and the medical field, with a particular focus on applications in cancer research, medical imaging, and diagnostics. Participants share various examples of how computational techniques are being integrated into medical practices and research.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants highlight the role of computer science in cancer research, specifically mentioning the development of software platforms for medical visualization and real-time data interaction.
  • Mathematical modeling is proposed as a useful tool for drug design, with suggestions for using mathematical or functional programming approaches.
  • Computer-assisted diagnosis (CAD) is discussed as a significant area of development, particularly in image analysis and integration of multiple imaging modalities for personalized medicine.
  • GPU-based Monte Carlo simulations are noted as important in radiation oncology, although the availability of quality biological data is seen as a current bottleneck in modeling cancer progression.
  • One participant shares an example of an internship opportunity related to the design and programming of heart pumps, illustrating practical applications of computer science in medical technology.
  • Integration of patient records, billing, and appointment systems into a single program is mentioned as another area where computer science can enhance medical practice.
  • Participants reference ongoing innovations in diagnostics, including CAD applications in mammography and challenges in digital pathology and imaging reconstruction algorithms.

Areas of Agreement / Disagreement

Participants express a variety of views on the applications of computer science in medicine, with no clear consensus on specific methodologies or areas of focus. Multiple competing perspectives on the effectiveness and current state of technologies like CAD and digital pathology are evident.

Contextual Notes

Some discussions touch on the limitations of current technologies, such as the need for quality biological data in cancer modeling and the infancy of digital pathology, but these points remain unresolved.

Who May Find This Useful

This discussion may be of interest to individuals involved in medical research, computer science applications in healthcare, and those exploring innovations in medical imaging and diagnostics.

Niaboc67
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Please describe how computer science and the medical field can work together. Anything dealing with cancer research would be greatly appreciated.
 
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Here are some links to check out.

http://folding.stanford.edu/
https://www.biostars.org/
http://bmi.stanford.edu/

Also for what it's worth, the group I am working with a my University does research in graphics and visualization, and some of their grad students are specialists in medical visualization.

I'm currently working for that group developing a software as a service platform for their volume rendering software, and from which to continually add new algorithms and features they develop, so that their collaborators at medical schools can have easy access.

The collaborators are radiologists and biomedical engineers. They have a lab where they invent and build new machines for imaging. They generate complex data sets and rely on computer scientists to design algorithms and build software which allows you view and interact with the data in real time.
 
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Mathematical modelling should be useful for designing medical drugs. For that, mathematical/functional programming should come to mind.
 
Computer-assisted diagnosis (CAD) - the development of algorithms for systematic analysis of images was very hot at the RSNA meeting a few years ago - and I suspect that it will be for years to come. This field will incorporate a lot of image registration work, as researchers and doctors will be needing to bring together information from multiple imaging modalities and use that for a more personalized, or patient-specific approach to medicine.

GPU-based Monte Carlo simulations have also been hot over the last few years. We use these a lot in radiation oncology.

Modelling of cancer progression and response to treatment is also a big field, although the computational side of things isn't really the bottleneck right now (it's more the availability of quality biological data).
 
I was recently offered an internship involving the design and programming of heart pumps - the programming part is a great practical example of the CS and medical fields working together. I was already in the middle of a project, though, and couldn't accept this enticing offer :(
 
Combining patient physiological & structural treatments records, billing, and appointment setting all in one integrated program.
 
You may be interested in researchers like Franziska Michor: http://michorlab.dfci.harvard.edu

If you are interested in more direct uses of computation, there are roles in both diagnostics and therapeutics.

I don't know much about therapeutics, but as Choppy said, on the diagnostics side there is CAD, including image segmentation, registration, and the recognition of lesions. CAD is widely used in mammography but not so widely used elsewhere yet. Digital pathology, which is one of the most complicated fields to digitize, is still in its infancy.

In CT and nuclear medicine, there is innovation ongoing in the areas of reconstruction algorithms.
 

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