Dying to care
Quote from the Wellcome Trust’s very helpful newsletter (SPIN)
“Medics argue that autopsies should be seen as “part of the whole care package” for patients.”
Well I know what they mean but out of context…… Just dope the dull York economists don’t get their QUALIES out to check whether we really should move over to autopsy as an initial investigation.
[the real story is that the number of autopsies has been dropping for many years and they are a very important way of determining what really was wrong with a patient—an important antidote to doctors' egos]
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From the BBC
“I am now the happiest woman on earth. When you marry a man with 86 wives you know he knows how to look after them,” she said.
There must be a flaw in this consumerist argument….
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Well there may be plenty of places but none of them nice.
Ben Wizner, an American Civil Liberties Union lawyer who is an observer here, said the experiences of Mr. Tabarak and Mr. Hamdan seemed to underscore the contradictions of the legal system here.
Mr. Wizner said there was a more fundamental contradiction underlying the trial. The Bush administration insists that even if a detainee is acquitted, officials could hold him indefinitely.
“Where else in the world,” Mr. Wizner said after court one day, “is someone being prosecuted for a crime who is already serving a life sentence and will continue to serve one if he’s acquitted?”
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Tags: USA
Finish privacy
Ross Anderson has a blog entry about a recent Finnish case here
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Tags: database, health, NHS, security
Honorable mention
Strange phrase but I am learning that the computing and informatics community do things differently. Anyway our poster—work largely done by an undergraduate computing student Steven McDonagh—received an Honorable Mention at the Medical Image Understanding and Analysis 2008 meeting.
Using 3D information for classification of non-melanoma skin lesions
Steven McDonagh, Robert B. Fisher and Jonathan Rees, University of Edinburgh
Filed under: computing, informatics, medical research, medicine | 0 Comments
Tags: 3d, AI, computer vision
It is summer and I like to afford myself some time for scholarship—summer for a clinical researcher should be an ethics application free zone. And more.
I have been fascinated for at least the last several summers by work on causal models. This time around I am dipping into the field following a few verbal spats with my former colleague, and friend, Bruce Charlton. Bruce likes some of the IQ field and thinks that major wrongs are being done to the study of genetic determinants of IQ by political correctness and ignorance. I think he is right about this latter point, but I don’t agree with many of his other views on this topic.
I have long been puzzled by why in some areas of human endeavour progress is made whereas in others—even when the procedures of enquiry seem similar—little advance occurs. I think even within a narrow area like medical research application of the same apparent rigour leads to advance is some areas and not others. There are lots of reasons for this, timeliness, new gadgets, topicality and so on. But a basic one is that the assumptions of the tools you use are not equally valid in different domains. Many economists like to parade their mathematics but they are just not nearly so good at explaining the world as physicists are. They just don’t do laws in the same way.
Anyway the prompt for this entry was a wonderful essay by Clark Glymour called ‘What went wrong? Reflections on Science by Observation and the Bell Curve’. He is blisteringly funny and smart but the point of the essay is to point out how many of the statistical techniques commonly used in certain fields (some psychology and much social science) are not up to the job people demand from them. The everyday regression analysis and the not so everyday factor analysis are just not appropriate. Instead he extols the virtues of ‘causality’ and thinking using the terminology of causal graphs (for more see here, here, here and here). A few quotes that make me chuckle:
‘That promise was kept for two statistical enterprises, hypothesis testing and parameter estimation, which for decades were the cynosure of the professional statistical study, but it failed in the more important parts of social inquiry that decide which parameters to estimate and which hypotheses to test.’
‘We are left with enterprises that use the most rigorous possible methods to estimate parameters in causal models that are often produced by whimsy, prejudice, demonstrably unreliable search procedures….’
‘A household is a business given over to caring for small, temporarily insane people, a business subject to cash-flow problems, endless legal harassments, run by people who expect to have sex with each other, who occupy the same space, and who go nuts when either party sex with anyone else.’
And on the over-credentialising of society (needing a PhD to take the litter out..) he puts the blame where it belongs.
‘The blame is with universities and college professors, who profit from every legal restriction that requires or rewards formal education’
Filed under: education, medical research, science, statistics | 1 Comment
Tags: causal models, Clark Glymour, intelligence, IQ
Unlike CED (see previous post) PLoS journals are open access and I can do what I like with what I write. Here is a recent article written about another piece here. It is all freely available to download. The intro is below.
Intro……
Cutaneous malignant melanoma (MM) falls into two main groups, based on aetiology [1–3]. First, a small minority of patients have acral MM, in which the disease occurs on the palms and soles. The incidence of acral MM is similar in people with widely different skin colours (and hence with different amounts of skin melanin), and at different latitudes. The palms and soles have a thick epidermis, and so few harmful photons of ultraviolet radiation (UVR) will penetrate to the germinative layers. Acral melanomas are therefore not believed to be causally related to UVR, and their aetiology remains a mystery. They will not be discussed further in this article.
By contrast, more than 90% of MM occurs on non-acral sites and is thought to be caused by UVR [2,4]. The evidence for such causality comes from a variety of fields. MM is most common in those with pale skin, which has a relative lack of melanin, a substance that blocks photons from penetrating deeply into skin [2]. African people with very dark skin are hundreds of times less sensitive to the harmful effects of UVR than white Northern Europeans. Even within white Northern European populations, MM rates vary in relation to more subtle degrees of difference in sun sensitivity. Those with red hair, pale skin, and a tendency to freckle are about three times more likely to develop MM than those without these three features [2,5]. The dramatically elevated rate of MM in those with European ancestry in Australia is therefore what we would expect: susceptibility of the host coupled with enhanced environmental exposure leads to a high disease risk [4].
Filed under: dermatology, medicine, melanoma, science, skin cancer | 0 Comments
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