Tara Retson Profile
Tara Retson

@Intraaxial

Followers
236
Following
330
Media
12
Statuses
251

Research resident in radiology at UCSD/neuroscientist learning deep learning. Let's talk tech, dessert, policy, or about how amazing the world can be.

San Diego, CA
Joined September 2016
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@Intraaxial
Tara Retson
9 months
Thank you so much for joining tonight! #RadAIchat.
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@Intraaxial
Tara Retson
10 months
Another recommendation: Variability among risk classification models – perform the same at a population level, but very differently for individuals. #RadAIchat.
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@Intraaxial
Tara Retson
10 months
Good study: Many studies have generalizability and bias issues, but in general AI + Human seems to be the most effective combination. #RadAIchat.
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mdpi.com
Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no signif...
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@Intraaxial
Tara Retson
10 months
Important study to be aware of: RCT in Sweden on AI in screening mammography. Note different screening practices: 2D (versus mostly DBT in US), double reading and longer screening interval. - Dr. Milch #RadAIchat.
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@Intraaxial
Tara Retson
10 months
I've been thinking AI should fully write the reports, especially for low risk/ negative exams (e.g. benign calcifications, biopsy marker, post-surgical change) and the rad just opens the study, reviews, and signs. This could also apply to US, MRI, biopsies, etc. #RadAIchat.
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@Intraaxial
Tara Retson
10 months
T4 There are risk percentages associated with many of the BI-RADS descriptions, it would be cool if someday these could be automatically read from our reports and calculated. OR… keep it simple and just edit my MRI dictations! #RadAIchat.
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@Intraaxial
Tara Retson
10 months
Such a great question! I think the main key here is FEWER MARKINGS. Historical CAD had too many markings which were a distraction, and ultimately led to decreased accuracy with CAD. - Dr. Milch.#RadAIchat.
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nejm.org
Computer-aided detection identifies suspicious findings on mammograms to assist radiologists. Since the Food and Drug Administration approved the technology in 1998, it has been disseminated into p...
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@Intraaxial
Tara Retson
10 months
Dr Yala is the Mirai risk model expert, but this paper recently came out investigating some of the features it used to make decisions.
pubs.rsna.org
Using bilateral dissimilarity as a mammography marker of near-term breast cancer risk, AsymMirai, a simplified deep learning bilateral dissimilarity–based model, performed similarly to the state-of...
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@Intraaxial
Tara Retson
10 months
As the technology proves itself, mammographers may start to convert. Making sure we educate our residents about the benefits and limitations of AI would help, and ultimately explainability would be key. #RadAIchat.
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@Intraaxial
Tara Retson
10 months
2/2 Instead, we have to wait for every new static version to get approved by FDA and then implemented - Dr. Milch #RadAIchat.
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@Intraaxial
Tara Retson
10 months
1/2 A big problem is that the FDA only approves AI tools that are "static" meaning they are not continually learning. A continually learning model would be more effective and more efficient. #RadAIchat.
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@Intraaxial
Tara Retson
10 months
There are no prospective randomized trials demonstrating effectiveness in real-world settings, thus many practices are hesitant to adopt without high quality evidence (specifically, no trials in the US) - Milch #RadAIchat.
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@Intraaxial
Tara Retson
10 months
T2 - Right now the radiologist is still responsible for the final read, so we have to trust AI and understand its strengths and weaknesses. At the same time, we need to be concerned about trusting it too much and falling into an automation bias trap.#RadAIchat.
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@Intraaxial
Tara Retson
10 months
T1- Also potential for AI to assist in appropriate orders by referring physicians, streamlining patient visits, quality assessment of technologist image acquisition - Dr. Milch #RadAIchat.
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@Intraaxial
Tara Retson
10 months
T1- Easy to forget that there are non-diagnostic things that would make our lives easier. Scheduling, checking on follow ups, dealing with insurance approvals. #RadAIchat.
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@Intraaxial
Tara Retson
10 months
Not sure what to add to @heacockmd, but Great article that summarizes some of the existing uses for AI outside mammo. #RadAIchat.
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@Intraaxial
Tara Retson
10 months
Hello! I am a breast imager from UC San Diego, and have been fascinated with AI since 2017. Excited to be part of tonight's chat as your moderator. Tonight I will also be sharing Dr. Milch’s tweets from my account. #RadAIchat.
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@Intraaxial
Tara Retson
1 year
Do you forsee these technologies having an impact on the training of ED or neurosurgery residents? We think a lot about overreliance on AI in rads, could that be the case for other specialists too? #RadAIchat.
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@Intraaxial
Tara Retson
1 year
AI and the brain, my two favorite things. Can't wait to hear from the neurosurgery perspective tonight. Hello from San Diego! #RadAIchat.
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@Intraaxial
Tara Retson
1 year
#RadAIchat can't wait for tonight's topic! I always have such a great reading list after these chats. Hello from San Diego!.
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