Fuzzy Firing Rule in Medical

8/4/2019 Fuzzy Firing Rule in Medical

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What is Fuzzy rules

A fuzzy rule can be defined as a conditionalA fuzzy rule can be defined as a conditionalstatement in the form:statement in the form:

IfIfxx isis AA THENTHEN yy isis BB

wherewhere xxandand yyare linguistic variables; andare linguistic variables; and AAandand BB are linguistic values determined byare linguistic values determined byfuzzy sets on the universe of discoursesfuzzy sets on the universe of discourses XXandand YY, respectively., respectively.

If called antecedents and then calledIf called antecedents and then called


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A fuzzy rule can have multipleA fuzzy rule can have multipleantecedents, for example:antecedents, for example:

IFIF project_duration is longproject_duration is long

AND project_staffing is largeAND project_staffing is large

AND project_funding is inadequateAND project_funding is inadequateTHEN risk is highTHEN risk is high

IF service is excellentIF service is excellentOR food is deliciousOR food is delicious

THEN tip is generousTHEN tip is generous


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OR Multiple ConsequentsOR Multiple Consequents

IFIF temperature is hottemperature is hot

THEN hot water is reduced;THEN hot water is reduced;

Cold water is increasedCold water is increased


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Fuzzy Rules relate fuzzy

setss Fuzzy rules relate fuzzy sets.Fuzzy rules relate fuzzy sets.

s In a fuzzy system, all rules fire to someIn a fuzzy system, all rules fire to some

extent, or in other words they fireextent, or in other words they firepartially. If the antecedent is true to somepartially. If the antecedent is true to somedegree of membership, then thedegree of membership, then theconsequent is also true to that sameconsequent is also true to that same

degreedegree.


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EFFECTIVE ANALYSIS

AND DIAGNOSIS OFLUNG CANCER

USING FUZZY RULES


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IntroductionLung diseases are the second most dangerous disease

in the world However there are many effective medicines which can

treat these lung diseases, the danger is that thepatients always ignore some initial symptoms of lung

diseases and they are only afraid when those symptomsare likely clear. But at that time, it seems to be moredifficult to treat those diseases.

In diagnosing lung diseases, doctors have to cope withmany difficulties, the patients symptoms are usually

not clear; the similarities in some lung diseasessymptoms are difficult to distinguish.

Doctors always have to test many times before makinga decision. So the diagnosis result depends on not onlypatients symptoms but also the doctorsexperiences.

Wrong decision means wrong treatment and the patientwould suffer more


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Proposed workIn this technique is used to determine the disease

name, stage and the diagnostic treatment usingthe algorithms and a rule base (developedspecifically for a disease).

Here the physician will take the symptoms of a

patient as input and based on his symptoms properdiagnostic treatment will be prescribed to apatient.

Each symptom has its own priority value and

physician will assign membership values to thelinguistic variables i.e. slight, low, medium, highand critical

The algorithm developed uses the rule base to

determine the disease name based on thes m toms entered b the user


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Continued..

Based on the severity of the symptomsentered the algorithm calculates the totalmembership of the symptoms and the

threshold value for this total membership. Then it creates the ranges which represent

the different stages of cancer such asprobable, low, medium, high and critical.

The diagnosis logic based on these results(i.e. the disease name and the stage) and therule base developed determines theappropriate diagnostic treatment for thepatient.


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Algorithm 1

1.) Take input from user as symptoms and theirseverity.

2.) Analyze symptoms using IF-Then rules(consisting of sets of symptoms) for possibledisease (individual rule for separate diseases.)

Example:-

IF (Cold Like Symptoms, Fever, Chills, Throat Pain,Pneumonia, Wheezing) THEN Disease = Bronchitis.

IF (Dry Cough, Wheezing, Shallow Breath, ChestPain) THEN Disease = Bronchial Asthma.

3.) Calculate threshold value on basis of symptomsentered.

Threshold U = No. of Symptoms * Total No. ofStages.


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4.) Calculate total membership as:mv = (mv * mv)/(No. of Stages/4)Where mv = sum of severities of all

symptoms.5.) Calculate disease stage using threshold value

and the severity value of the symptoms (using theintervals

created based on the symptoms.)t0 = (l + ((u) / 14)); // No Cancert1 = (l + ((u) / 12)); // Probable Staget2 = (l + ((u) / 10)); // Low Stage

t3 = (l + ((u) / 8)); // Medium Staget4 = (l + ((u) / 6)); // High Staget5 = (l + ((u) / 4)); // Critical Stage6.) Store the input and the result (disease and

stage) into database and display result to the user


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Algorithm 2

STEP1:Select n number of symptoms i.e. Population or

Operational data

Assign some priorities values (weight) to the

symptomsFor eg psymptom i=pi , where i=1 to n

STEP2:

Now choose the severity for symptoms and assign

some membership values to the linguistic variables:

Very low=0, low=0.25, medium=0.5, high=0.75,very high=1

Symptom i=very low||low||medium||high||very high


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STEP3:Calculate the total value i.e supportTotal=

STEP4:Now calculating high and low values

Highvalue :Lowvalue

STEP5:Now calculating the membership function i.e

fuzzy value(FV)FV=Total value/Highvalue(total weight)(Or) we can say Support(Highvalue)=FV

STEP6:Now dividing into N ranges between high and

low valuesB (i+1) = lowvalue + (k * highvalue / N)where k = 0 to N and I =0 to N.


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STEP7:Now CheckFor each i=0 to N-1

If(total >= b(I + 1) && total < b(I + 2)) ThenStage=Sj where j=1 to N+1Else if (total==b(i+2))Then stage=N+2STEP8:Now checkFor each j=1 to N+1if(stage.equals("Sj")){ cancertype="type j"; treatment="treatment j";}else{cancertype="type N+2";treatment="treatment N+2";}


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conclusionMedical diagnosis using this system are highly

accurate and provide information in a wide rangeof formats (text, images, clusters etc.)This system is compatible with other techniques as

the database can be used with case based

reasoning and other mining methods. Thiscapability of the system increases the scope andage of the system.This system is useful to the physician as well as the

user for determining the type of lung cancer and

the stage of the cancer. This system is based on asimple algorithm and hence the accuracy is low.The accuracy can be increased by implementingmore analysis techniques on the same databaseused in this system along with the current

algorithm


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Thank you

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Fuzzy Firing Rule in Medical