Numbers. I’ve read thousands of resumes over the past few months, screened dozens of applicants, and experienced a wide variety of weirdness and fakes both in resumes and on screen calls. Please note that I’m talking about raw “application box resumes”. Referrals and other semi-vetted sources don’t get this level of scrutiny.
I gave two examples of secondary sources, but what I’m really getting at here is that the numbers and noise are so, so high now (not to mention staffing firm fronts and foreign actors) that I usually need more signal than a solid-looking resume before investing even 30’ in a screening call.
Seconding. These days I will rarely talk to anyone without a verified LinkedIn or other presence like a clearly inhabited GitHub (and I’m not looking for hyperactivity by any means)
TeleMed [1] is slightly higher-end and has CE mark (IIRC in the $1-2k range for the uncleared/demo version). UltraSonix [2] used to be relatively reasonable option (IIRC under $10k), but they were bought by BK and prices may have increased.
> For extra points, have alignment sticker targets you can attach to the body to track the patient if they move
This is roughly how surgical navigation systems work. The leaders in this area are companies like BrainLab and Medtronic, usually using optical tracking sensors (e.g. from Northern Digital), or sometimes electromagnetic, with accuracy in the 1-5mm range. For neurosurgery (the area I'm most familiar with), several companies offer tracked ultrasound integration, usually for live overlay and comparison with pre-operative MR or CT images.
> combine it with the positioning sensors of a VR system
For any folks interested in this, there is an active, excellent open source project called PLUS focused on ultrasound, tracking, and sensor data acquisition, as well as volume reconstruction [2]. There's also an associated 3d visualization ecosystem [3].
> This is the same misconception I have been trying to dispel. The null hypothesis is not the inverse of that "layman's" statement, it is a specific set of predicted results calculated in a very specific way.
The entire point of this discussion is that the software is not calculating the null hypothesis that users expect. That the current model it does in fact calculate is internally-consistent is tautological and irrelevant (though actual bugs were found in at least one package).
> Describing the problem as excess false positives is confused, because these are true positives.
This is deeply wrong. A "true positive" in this context would mean that the resting brain activity of multiple subjects is actually correlated with arbitrary length, randomized, moving test windows. Again, the data is untreated; they are imposing arbitrary test windows and looking for increases in brain activity (increased image intensity) correlated with the stimulus-ON sections of the pseudo-treatment.
From reading some of your prior comments on the subject, it seems prudent to point out that the causal link between stimulus and BOLD effect is quite literally observable: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3130346/
FWIW, typical raw fMRI data is mostly useless unless you know the design parameters of the study (stimulus timing, imaging onsets, etc.). Though there are some interesting data-driven analyses techniques, especially for resting-state data.
Many research studies in the U.S. are required to do "structural" scans (high-resolution T1 or T2) and send them to a safety read by a radiologist, for liability reasons. At very least, this scan should be available directly from the hospital imaging department. If you are lucky all the data will have been sent through the hospital PACS and the imaging department will indiscriminately dump everything. At a research-only center it might be more complicated because such images are likely sent off-site for the safety read.
I gave two examples of secondary sources, but what I’m really getting at here is that the numbers and noise are so, so high now (not to mention staffing firm fronts and foreign actors) that I usually need more signal than a solid-looking resume before investing even 30’ in a screening call.