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Medical Researcher Rediscovers Integration
parallel_prankster writes "I find this paper very amusing. From the abstract: 'To develop a mathematical model for the determination of total areas under curves from various metabolic studies.' Hint! If you replace phrases like 'curves from metabolic studies' with just 'curves,' then you'll note that Dr. Tai rediscovered the rectangle method of approximating an integral. (Actually, Dr. Tai rediscovered the trapezoidal rule.). Apparently this is called 'Tai's Model.'"
First, does anyone have a link to the actual article? TFS only seems to include an abstract. Second, this was published in 1994. Third, while it may simply seem that the author is rediscovering integration, the field of numerical integration is actually a rather rich one. It's all well and good to say "take an antiderivate and evaluate at the endpoints", but for a function that is found experimentally this is essentially nonsense. While the submitter here claims that this article is simply rediscovering the trapezoid rule, there's actually no such evidence given in the Abstract--algorithms for determining how big of rectangles/trapezoids/etc to use in your calculations is actually an active area of research (albeit usually for the multidimensional case) and it is possible that this researcher did actually discover a better algorithm for deciding how to do the numerical approximations.
Really it should be under idle, it's just the fact that the dude forgot all about calculus and went back and remade the approximate method of integration. His hubris must be punished by way of an Internet meme.
Eat sleep die
Nothing spoils the joy of having an original idea more than discovering it's actually a basic concept of another discipline.
Given that this is highschool - level math, I'd say "reinventing" it primarily shows a shocking lack of education (for a doctor).
Or evidence of having cheated his way through school like well over half of premeds [citation needed].
No better way to learn than to discover it yourself. You'll never forget Euclid's algorithm, but I have to look it up every time.
You may laught at this, but you find the same thing in all fields. Programming language designers are writing papers on decades old language features, user interface researchers are getting lots of citations for decades old ideas or gimmicks from scifi movies, and theoretical computer science authors are woefully ignorant of statistics and machine learning. Mathematicians and physicists aren't immune either.
Doctors tend to complain that they can only afford a "modest lifestyle" but tend not to understand what they have is generally well above "modest."