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Breast Cancer Detection Based on Hybrid Features Using Machine Learning Classification Techniques

Thesis Info

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Author

Ayaz Ahmed Hashmi

Institute

Virtual University of Pakistan

Institute Type

Public

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2019

Thesis Completion Status

Completed

Subject

Software Engineering

Language

English

Link

http://vspace.vu.edu.pk/detail.aspx?id=337

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676721027384

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The breast cancer in the women is most commonly diagnosed type of cancer. The mortality rate can be reduced if proper and early breast cancer treatment can be made. Masses and microcalcification contain very important diagnostic information in breast cancer. There is great variation in masses and micro-calcifications so, radiologists face difficulties in proper diagnosis of the breast cancer. Researchers in the past developed efficient systems based on computer aided diagnostic (CAD) systems. Moreover, relevant feature extraction plays a vital role in proper diagnostic and prognostic. Based on the diverse nature and variations in the breast cancer mammograms, we propose hybrid feature extraction approach including morphological, entropybased features, elliptic Fourier descriptors (EFDs), texture and scale invariant feature transform (SIFT). For improving the detection accuracy based on the extracted features, we applied machine learning classifiers including Support vector machine (SVM) alongwith its kernels such as Gaussian, radial base function (RBF), polynomial; Na?ve Bayes and Decision tree (DT). The validation was measured using 10-fold cross validation (CV) system. For a performance evaluation, we computed different metrics including specificity, sensitivity, false positive rate (FPR), negative predictive value (NPV), positive predictive value (PPV), and area under the receiver operating curve (AUC). Both combination and single feature are used as an input for classifiers. The results reveal that both single and combination of features provides higher detection results. Thus, the new feature extracting approach is more robust in early detection of breast cancer.
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Devasahayam: The First Martyr For Jesus Christ In Travancore

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Inflation Structure and its Determinants in Pakistan With Reference to Agriculture Sector

Inflation affects distribution of income both and wealth. Nominal incomes of some individuals tend to increase with others remain constant inflation, while those of change in the distribution of thus causing a income in favour of group. During early 1970s, it was realized the former the complex that and multidimensional problem of inflation needs a systematic and scientific understanding, examination, investigation and analysis. This study was undertaken to analyze process in Pakistan with reference monetarist, structuralist and the inflationary agriculture to combined and sector. agricultural bottleneck models were used in the analysis of data. A 27 variables were used for Pure the analysis. In all total of the models, annual growth rate in wholesale price index, consumer price index and implicit GNP deflator were considered as dependent variables and regressed with different combinations of variables to examine the effectiveness of these variables on inflation. In monetarist model, Supply), V10 (Annual V5 (Annual Growth Rate year In lag) were found to increase structuralist model, [International + Inter-wing) the V17 one in Consumer Price Index inflation rate. (Imports as per cent of vii in Money in Wholesale Price Index year lag), and Vll (Annual Growth Rate one Growth Rate GNP), + V19 Exports (Extent of ''HP the Non-Con in odity for Incremental Growth in GDP Accounts Producing Sectors), V24 {Indirect Tax Revenues as per cent of and V 2 5 were Taxes in Total Taxes) (Share o£ Indirect variables mostly found causing inflation, whereas, V27 Remittances as per cent of GNP) seemed the to decrease GNP) the ( Hone level of inflation. that V18 While combining the above two models, it was found and V23 (Divergence between (Annual Growth Rate in Import Prices) Inflation Food inflation, Prices while enhanced Index), Price Remittances as per (Home V27 declined significantly Overall and inflation the as home cent of the GNP) remittances increased. The study depicted V22 (extent of excess that the variable on agriculture sector Demand for Food) did not significantly increase inflation. However, it was found that not support inflation in the the variable does structuralist model, while in combined model it does. Results indicated that less than half of the inflation 1 1 experienced by Pakistan over the period 1939-60 to 1979-80 could il be ii attributed to in terna t iona 1 domestic policy action greater factors to reduce and the rate thus of the scope for inflation was than what was thought to have been the case until now. Further studies in the areas of domestic supply of agriculture commodities, imports and exports of agricultural output were suggested in Pakistan to determine the actual inflationary movements and pertinent policy implications,