Posts tagged medicine
The Microlab is a do-it-yourself Controlled Lab Reactor (CLR). You don’t need a CLR to make chemical reactions happen, but it makes the process of synthesizing compounds from precursors much easier and more reliable.
The Microlab is designed to load a recipe for a chemical reaction, then automate the temperature control, reagent addition, and stirring that are needed. It is designed for small-molecule organic chemistry to make certain medicinal compounds in your own home or workshop.
“It is well known that intracranial lesions can be associated with psychiatric symptomatology. But this is he first and only instance I have come across in which hallucinatory voices sought to reassure the patient of their genuine interest in her welfare, offered her a specific diagnosis (there were no clinical signs that would have alerted anyone to the tumour), directed her to the type of hospital best equipped to deal with her problem, expressed pleasure that she had at last received the treatment they desired for her, bid her farewell, and thereafter disappeared.”
–A difficult case: Diagnosis made by hallucinatory voices
Healthcare costs less and performs better when societies pull together. Unfortunately, Icelandic conservatives want American inefficiencies.
via https://medium.com/@smarimc/universal-coverage-is-good-economics–8ea87e9d33c9
While the bleeding process is clearly better for the crabs than the outright harvesting that used to occur, the study shows that there’s no such thing as free horseshoe crab blood.
http://www.theatlantic.com/technology/archive/2014/02/the-blood-harvest/284078/
For one British university, what began as a time-saving exercise ended in disgrace when a computer model set up to streamline its admissions process exposed - and then exacerbated - gender and racial discrimination. As detailed here in the British Medical Journal, staff at St George’s Hospital Medical School decided to write an algorithm that would automate the first round of its admissions process. The formulae used historical patterns in the characteristics of candidates whose applications were traditionally rejected to filter out new candidates whose profiles matched those of the least successful applicants. By 1979 the list of candidates selected by the algorithms was a 90-95% match for those chosen by the selection panel, and in 1982 it was decided that the whole initial stage of the admissions process would be handled by the model. Candidates were assigned a score without their applications having passed a single human pair of eyes, and this score was used to determine whether or not they would be interviewed. Quite aside from the obvious concerns that a student would have upon finding out a computer was rejecting their application, a more disturbing discovery was made. The admissions data that was used to define the model’s outputs showed bias against females and people with non-European-looking names.
http://www.theguardian.com/news/datablog/2013/aug/14/problem-with-algorithms-magnifying-misbehaviour
