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Admission Essay For Radiology Program

H.Y.K. Sure. Today we’ll be discussing the paper that you and your colleagues wrote on “Automated Critical Test Findings Identification and Online Notification System Using Artificial Intelligence in Imaging.” It’s a very promising topic indeed and I must share with you that yesterday as I normally do I woke up to National Public Radio, but I woke up very abruptly because what I heard on the radio was some informatics expert pontificating that artificial intelligence meant the end of radiology as we know it. Happily the piece also included a discussion by members of the data science group at Mass General Hospital who put it into better perspective noting that artificial intelligence was a tool that would enhance radiologists function but not a primary threat at this time. So I’m sure everybody will be interested in your paper and the discussion of it. So first what actually is deep learning and if you could define that that would be helpful.

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Radiology Technologist Essay - 1170 Words

Radiology admission essay - Especializo

Herbert Y. Kressel, MD: Hi. This is Herb Kressel and welcome to the November 2015 Radiology podcast. This month we have discussions on three provocative manuscripts. First I'll be interviewing Dr. Matthew McInnes from the University of Ottawa who with his colleagues performed an interesting, systematic review on the accuracy of gadoxetic acid enhanced MRI in the diagnosis of focal nodular hyperplasia and hepatocellular adenoma. They came up with a rather interesting result that sheds some important light on the issue of disease classification and the role of systematic reviews in meta-analysis. Next, my colleague Dr. Alex Bankier, a Deputy Editor for thoracic imaging, will be speaking with Dr. David Yankelevitz who with colleagues from the International Early Lung Cancer Action Program provided a provocative report on the screening of non-solid nodules in baseline and annual repeat rounds. They have some rather interesting findings to discuss with Dr. Bankier. Finally, my colleague Dr. Albert de Roos, our Deputy Editor for cardiovascular imaging, will be speaking with Dr. Michael Brand of the University Hospital at Erlangen, Nuremberg on their paper on the influence of cardiac MRI on DNA double strand breaks in human blood lymphocytes. As you may know, there's a controversial article published by another group noting the presence of these breaks and speculating on the safety of cardiac MRI. This report has somewhat differing results and I think you'll find the discussion very worthwhile. As always we welcome your comments and thoughts on this month's podcast.

D.M. Well I think you know this study was done at the VA and they have one thing that really facilitated this study that is not present throughout the rest of the country necessarily and that is the use of these structured suspicious for malignancy codes. And really that's what allowed us to take what might be coded as an abnormal radiograph or CT scan and narrow it down to just the subset that we're really looking at, and in some places they don't even use their normal codes so that would make it even more difficult for this trigger to be put in place. So I think as radiologists, probably the next step to make use of this type of software an algorithm and technology, is to kind of put together on a list of code that can be incorporated with the x-ray rather than just the text report and that allows researchers like me as well administrators and clinicians to make much better use of the data. So I think it's similar to how BI-RAD codes are done. I mean if you have a BI-RAD 2 it's very different from a BI-RADs 4, you kind of know exactly what you're looking at and if similar codes could be agreed on by radiologists and clinicians and probably in this case pulmonary specialists, I think that would be a great start in allowing this type of work from a research and a quality improvement prospective to proceed.

Radiology admission essay - Metodo Energhia

D.M. Well I think you know this study was done at the VA and they have one thing that really facilitated this study that is not present throughout the rest of the country necessarily and that is the use of these structured suspicious for malignancy codes. And really that's what allowed us to take what might be coded as an abnormal radiograph or CT scan and narrow it down to just the subset that we're really looking at, and in some places they don't even use their normal codes so that would make it even more difficult for this trigger to be put in place. So I think as radiologists, probably the next step to make use of this type of software an algorithm and technology, is to kind of put together on a list of code that can be incorporated with the x-ray rather than just the text report and that allows researchers like me as well administrators and clinicians to make much better use of the data. So I think it's similar to how BI-RAD codes are done. I mean if you have a BI-RAD 2 it's very different from a BI-RADs 4, you kind of know exactly what you're looking at and if similar codes could be agreed on by radiologists and clinicians and probably in this case pulmonary specialists, I think that would be a great start in allowing this type of work from a research and a quality improvement prospective to proceed.

R.S.B. Well I have two series of thoughts. We did a study and found the exact same results, but basically ours were data from a 15 percent to randomize trial across the U.S. We looked at the doses patients got to CT and five percent of patients got low dose studies and the range of doses for kidney stones, it should be two or three or four milisieverts ranged up to 75 milisieverts for one exam. So the results were probably more disappointing for me than for Jim because this was my study that I did not put close oversight into how the CTs were done and I feel terrible about it because I could have, but I thought well everyone knows you're supposed to use low dose for CT for stones. There was no education needed. I think there's enormous disconnect between what we know we should be doing and what we're doing. I think the reason for that is we haven't put any structured systems in place for making sure that people assess their doses and know what they're doing in comparative benchmark. I think there's really a role for more than telling people good practices or publishing papers in your journal and saying this is what you can do, I think rather we need to put much more clear expectations that in your patients you shouldn't have doses above that range and I think part of the difficulty is we have so many different names for different metrics, we haven't make it easy for people to really keep track and I think it's incumbent on us as radiologists to take the lead in this and really try hard to make it simple and I don't think it's that complicated saying these are the doses I use in my patients and this is what I should be doing and if I'm not reaching those milestones I need to do something different.

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Radiology admission essay CSU Dominguez …

J.A.B. You know actually I think that UC's data, UC's system should be complemented on their doses. They actually are lower in many areas than what we were appointed, but it's important to understand where DRL data came from in the U.S. because it's sort of a sad story. When we put together the NCRP Report 172 published in 2012 which defined DRLs for the United States, not just in CT but in radiography, nuclear medicine and fluoroscopy. We had very little data to draw upon unlike our counterparts in Europe which had been doing surveys of dose exposures for quite some time. We basically had two sources of data, the American College of Radiology CT Accreditation program data which of course is a skewed sample because these are data extracted from people who want to become accredited so it's a bio-sample. The other data came from the National Evaluation of X-Ray Trends sponsored by the Food and Drug Administration. This was the saddest thing because the FDA had last surveyed collected survey data for CT in 2005, 2006 through the CRCPD. That data had not yet been analyzed by the time we were writing our report and we basically had to ask them to analyze a subset of the data just to get some sense of it and they did a subset of 40 data points for us. I give big credit to Dave Spelic at the FDA who did this on his own and so basically years had gone by and the data had just languished without any analysis. So the U.S. has done a poor job in really producing data, survey data, for DRLs. Going forward I think the work that was done at the UC system for a local or regional registry or through the American College of Radiology through a national registry, will provide much more real time data from which we can look at DRLs and calculate DRLs and adjust them over time.

Essay on Technology. Research Paper on Radiology

J.A.B. You know actually I think that UC's data, UC's system should be complemented on their doses. They actually are lower in many areas than what we were appointed, but it's important to understand where DRL data came from in the U.S. because it's sort of a sad story. When we put together the NCRP Report 172 published in 2012 which defined DRLs for the United States, not just in CT but in radiography, nuclear medicine and fluoroscopy. We had very little data to draw upon unlike our counterparts in Europe which had been doing surveys of dose exposures for quite some time. We basically had two sources of data, the American College of Radiology CT Accreditation program data which of course is a skewed sample because these are data extracted from people who want to become accredited so it's a bio-sample. The other data came from the National Evaluation of X-Ray Trends sponsored by the Food and Drug Administration. This was the saddest thing because the FDA had last surveyed collected survey data for CT in 2005, 2006 through the CRCPD. That data had not yet been analyzed by the time we were writing our report and we basically had to ask them to analyze a subset of the data just to get some sense of it and they did a subset of 40 data points for us. I give big credit to Dave Spelic at the FDA who did this on his own and so basically years had gone by and the data had just languished without any analysis. So the U.S. has done a poor job in really producing data, survey data, for DRLs. Going forward I think the work that was done at the UC system for a local or regional registry or through the American College of Radiology through a national registry, will provide much more real time data from which we can look at DRLs and calculate DRLs and adjust them over time.

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