DENDRAL EXPERT SYSTEM PDF

Then, the machine sorts the chunks by passing them through a magnetic field which deflects the high-charge, low-weight ones more than it does the low-charge, high charges ones. This is called a mass spectrogram. By knowing the masses, it is possible to guess how the atoms of a single molecule of the unknown substance are put together. The generator consists of a structure enumerator and a synthesizer, which produce a synthetic mass spectrogram by simulating the action of a real mass spectrometer on each enumerated structure. The tester compares the real mass spectrogram with those produce by the generator.

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Then, the machine sorts the chunks by passing them through a magnetic field which deflects the high-charge, low-weight ones more than it does the low-charge, high charges ones.

This is called a mass spectrogram. By knowing the masses, it is possible to guess how the atoms of a single molecule of the unknown substance are put together. The generator consists of a structure enumerator and a synthesizer, which produce a synthetic mass spectrogram by simulating the action of a real mass spectrometer on each enumerated structure. The tester compares the real mass spectrogram with those produce by the generator.

The possible structure are those whose synthetic spectrograms math the real one adequately. MYCIN helps the physician to prescribe disease- specific drugs. Expert systems are restricted to a very narrow domain of expertise. For example, MYCIN, which was developed for the diagnosis of infectious blood diseases, lacks any real knowledge of human physiology. In fact, therapy prescribed for the blood disease might even be harmful because of the other disease.

Expert systems can show the sequence of the rules they applied to reach a solution, but cannot relate accumulated, heuristic knowledge to any deeper understanding of the problem domain. Expert systems have difficulty in recognising domain boundaries.

When given a task different from the typical problems, an expert system might attempt to solve it and fail in rather unpredictable ways. Heuristic rules represent knowledge in abstract form and lack even basic understanding of the domain area.

It makes the task of identifying incorrect, incomplete or inconsistent knowledge difficult. Expert systems, especially the first generation, have little or no ability to learn from their experience. Expert systems are built individually and cannot be developed fast. Complex systems can take over 30 person-years to build.

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Expert Systems: Dendral & Mycin

G Veera Raghavaiah. It is one of the early example of a successful AI program. It reasons backward from its goal of determining the cause of a patient illness. It uses its production rule4s to reason backward from goals to clinical observations.

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Examples of Expert Systems | Artificial Intelligence

Heuristic Dendral[ edit ] Heuristic Dendral is a program that uses mass spectra or other experimental data together with knowledge base of chemistry, to produce a set of possible chemical structures that may be responsible for producing the data. For example, the compound water H2O , has a molecular weight of 18 since hydrogen has a mass of 1. Heuristic Dendral would use this input mass and the knowledge of atomic mass numbers and valence rules, to determine the possible combinations of atomic constituents whose mass would add up to Thus, a program that is able to reduce this number of candidate solutions through the process of hypothesis formation is essential.

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Does the patient have a clinically significant allergic reaction to any antimicrobial agent? How much does the patient weigh? My first recommendation is as follows: to cover for items 1, 2, 3, 5 and 6, give gentamycin using a dose of mg 1. Modify dose in renal failure.

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