543 karma · joined July 29, 2010
You need to have a unique ID set in the header. You can do this in calibre.
Specifically, a unique 4 byte character sequence at the 32 byte offset in the header (MOBI header). See: http://wiki.mobileread.com/wiki/MOBI
If that's set (easy in calibre), you will sync across your devices.
It has been uniformly dismissed/ignored by the larger node.js community. Take from that what you will.
No need for Varnish for proxying your websockets.
The thing that I wish the project had was some official opinionated best practices guidelines. How to structure a growing app, build/minify workflow, pitfalls, etc. (Note: this wish may be due to my utter noobishness and I'm mostly monitoring the mailing list and reading all the questions to learn)
Other than that, I wish AMD was going to be supported in core, but tbranyen's requirejs use (shim) plugin is going pretty well.
http://www.hopkinsmedicine.org/kimmel_cancer_center/our_cent...
I always say that St. Louis is a nice place to be from. It's a nice place to raise a family. But I'm never going to move back. Or under extreme protest if my wife decides she wants to move back to be by family. There's just nothing interesting about St. Louis. White flight ruined the city in the sixties and highway 70 divides the majority black population (north) from the majority white population (south). So it's basically a segregated suburbia wrapped around a lifeless inner core. No one lives in the city. They drive there to work, drink and watch sports. Period.
I certainly wouldn't want to start a tech company there.
Our family room computer is a mac mini that is logged into one user account all of the time. It is shared by myself, my wife and my kids. The iPhoto on that account is set up to use my iCloud account. If my wife wants to get her photos (iPhone) downloaded from iCloud she has to log over to an account that only exists for this purpose.
So I'm sure the whole documents, todos, calendar and everything else on 10.8 is going to be a similar pain in the ass for people sharing one computer.
We have to manage three AppleIDs. My iCloud account, her iCloud account and we share an AppleID for purchases from the App Store. They need to fix this for multi-Apple families.
Those are the two non-starters for me with linux on a laptop. OSX just does an awesome job with both of these.
I was almost physically sick when that came across the air. I'm a long-time Democrat but I'll be damned if that didn't make me want to never vote for anyone ever again. Our two political parties are really two sides of the same coin and they are all working for corporations.
And javascript isn't that bad on the server when you're dealing with ES5 and not worrying about browser-specific js nightmare stuff.
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<!--[if lt IE 9]> css <![endif]-->I mostly said moderately differentiated, because for a lot of pathologists, if you give us a three tiered system for grading some type of cancer (and there are systems for almost every type of cancer) that we'll put most things in the middle. I personally believe two tiered systems work better for most everything. Most studies have shown that breast cancer scoring (in the US, most use the Nottingham modification of the Bloom-Richardson system) is only moderately reproducible anyways [1][2]
I tend to only fully grade the tumor after it has been resected, because there is not much point in grading it on the biopsy (ie. it won't change management, most patients are still going to have surgery) since sampling error may influence the final grade if you are discrepant from the biopsy.
I always tell friends and family that if they have any medical procedures, and most especially those for cancer, to always get copies of the operation note and the final pathology interpretation. The operation note will be written by the surgeon and will detail everything she did during the operation, what was removed, what was placed, etc. The final pathology will be the best place to get detailed information about what the tumor, where it is, the pathologic stage, etc. Your discussions with all of the other doctors will all basically be dictated by this report. There may be multiple of them, one for each procedure. So get the biopsy pathology report, the pathology report from the mastectomy, etc. They should also report out the results of the ancillary testing to (ER/PR/Her2) since they are the ones who did them. Most of the cancer reports (in the US anyways) should be written in accordance with the protocols from our professional organization and can be found online [3]. You'll probably find them somewhat tedious, but there is a wealth of information in there [4]. You are entitled to those reports and you really owe it to yourself to get a copy. If your doctor/doctor's staff won't get you one, then you could contact the pathology group directly to obtain one, don't hesitate.
In general, the grade of the tumor is far, far less important than stage of the tumor at diagnosis (most importantly the status of the axillary lymph nodes) and also the ER/PR/Her2 status of the tumor.
[1] http://www.ncbi.nlm.nih.gov/pubmed/15920556
[2] http://www.ncbi.nlm.nih.gov/pubmed/7856562
[3] http://www.cap.org/apps/cap.portal?_nfpb=true&cntvwrPtlt...
[4][pdf] http://www.cap.org/apps/docs/committees/cancer/cancer_protoc...
- Segregate tissue from non-tissue (ie. blank slide space)
- Classify the tissue (epithelial versus mesenchymal/stromal, mucin/matrix,
exogenous material, etc).
- Decide if it is normal or abnormal
- Decide if it is native to whatever organ that it reportedly came from or is it
a metastases from somewhere else.
- Select appropriate immunohistochemical stains or other ancillary tests (eg.
molecular assays).
- Appropriately interpret the immunohistochemical stain (eg. is it a nuclear stain
or cytoplasmic, or both, or membranous).
Is that staining true staining or artifactual.
- Interpret that in the clinical context of the patient's history.
I think at the end of my career, they will eventually haul my carcass off of my microscope (hopefully!) in 40 to 50 years hence. I imagine that we will have made a ton of progress with computer vision in pathology, and will be using it in an adjunct fashion. To help with analyzing results and other tedious tasks that computer vision is well-suited for. But a lot of medicine, and especially pathology, is making intuitive connections and conclusions with inconsistent and incomplete evidence in day-to-day work on individual patients.
With regards to the study, I will just point out that the system is not diagnosing breast carcinoma, but rather is producing a score which reflects the prognosis as relates to overall survival of the patient (so it is not as impressive as the somewhat hyperbolic HN title makes it out to be... a better title would be 'Stanford computer analyzes breast cancer more accurately than human doctor' which is not surprising at all given the well-documented interobserver variability in breast cancer scoring, particularly in moderately-differentiated tumors). That is to say that the computer already knows the tissue that it is looking at is a tumor and not benign breast tissue. Furthermore, it is really only providing a histologic (or morphologic) score, which is to say, that it is attempting to predict how aggressive the tumor will behave based upon how well or not well it is differentiated (how ugly it is). These days, this score is actually less useful in clinical practice than other information such as whether or not the tumor cells are expressing estrogen/progesterone hormone receptors, or if it is over-expressing Her2-neu protein, as these are possible paths for cancer therapy (anti-estrogen drugs vs. Herceptin) in addition to being prognostic indicators (tumors which express ER/PR generally behave better than tumors which are ER/PR negative and express Her2), as well as the stage (or how far the cancer has already spread) at the time the patient is diagnosed. There are a bunch of companies which are getting FDA approval for computer vision related algorithms for scoring immunohistochemical assays for ER/PR/Her2 [1].
So I am actually far less concerned about a computer doing my job very well, which is actually looking at a piece of tissue on a slide and making a tumor versus not-tumor distinction. This is very hard to do and I think will continue to be even harder for computers/computer-vision/AI to do for a long time to come. I am far more concerned about molecular diagnostics. That is the true-future for making cancer determinations and may even eliminate the part of my job where I tell you if something is benign vs. malignant.
[1] http://www.aperio.com/pathology-services/analyze-slides-auto...