A Novel Approach to Perform Analysis and Prediction on Breast Cancer Dataset using R

Basha, Syed Muzamil; Rajput, Dharmendra Singh; Iyengar, N. Ch. S. N.; Caytiles, Ronnie D.

doi:10.14257/ijgdc.2018.11.2.05

Cited by 17 publications

(7 citation statements)

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“…In research done by Basha et al [22], some liberated electrons, due to thermionic emission, get electrically attracted towards the anode. This collision onto the target (tungsten) results in photons' emission in X-Ray Spectrum, thereby forming the basis of X-Ray Image formation.…”

Section: Preprocessingmentioning

confidence: 99%

Covid-19 Detection from Chest X-Ray Images Using Advanced Deep Learning Techniques

Mahajan¹,

Raina²,

Abouhawwash³

et al. 2022

Computers, Materials &Amp; Continua

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Like the Covid-19 pandemic, smallpox virus infection broke out in the last century, wherein 500 million deaths were reported along with enormous economic loss. But unlike smallpox, the Covid-19 recorded a low exponential infection rate and mortality rate due to advancement in medical aid and diagnostics. Data analytics, machine learning, and automation techniques can help in early diagnostics and supporting treatments of many reported patients. This paper proposes a robust and efficient methodology for the early detection of COVID-19 from Chest X-Ray scans utilizing enhanced deep learning techniques. Our study suggests that using the Prediction and Deconvolutional Modules in combination with the SSD architecture can improve the performance of the model trained at this task. We used a publicly open CXR image dataset and implemented the detection model with task-specific pre-processing and near 80:20 split. This achieved a competitive specificity of 0.9474 and a sensibility/accuracy of 0.9597, which shall help better decision-making for various aspects of identification and treat the infection.

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Section: Preprocessingmentioning

confidence: 99%

Covid-19 Detection from Chest X-Ray Images Using Advanced Deep Learning Techniques

Mahajan¹,

Raina²,

Abouhawwash³

et al. 2022

Computers, Materials &Amp; Continua

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“…where as in [4] the author used gradient ascent algorithm in finding out the exact weights of the terms used in determining the sentiment of tweet and used Boosting approach to improve the accuracy of linear classifier. In [5], the author provide a novel way of performing prediction on Breast cancer dataset, compared the performance of three different feature selection algorithm and proved that genetic algorithm is giving best result in selecting the best feature among all the available feature. SVM algorithms gives the best result in predicting the level of certainty in breast cancer.…”

Section: Literature Reviewmentioning

confidence: 99%

Data Exploration on Overall Suicides Cases Registered Across India

Teja¹,

Pravalika²,

Varshitha³

et al. 2018

IJUNESST

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“…where as in [21] the author used gradient ascent algorithm in finding out the exact weights of the terms used in determining the sentiment of tweet and used Boosting approach to improve the accuracy of linear classifier. In [22], the author provides a novel way of performing prediction on Breast cancer dataset, compared the performance of three different feature selection algorithm and proved that genetic algorithm is giving best result in selecting the best feature among all the available feature. SVM algorithms gives the best result in predicting the level of certainty in breast cancer.…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing the performance of Various Fraud Detection Techniques

Anamika¹,

Mayuri²,

Reddy³

et al. 2018

IJSIA

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Sales of a product plays a vital role, towards profitability of any organisation. It helps in building trust and allegiance between customer and business. Sales department in any organisation help us to build a strategic decision for growing their business. In the process of building a strong relationship, there is chance of performing fraud, termed as sales fraud. Detecting such fraud can be of great help to the organization and taking appropriate steps to prevent the same in future. In this paper, we have implemented various clustering techniques like, k-means, k-modes, Hierarchical clustering, partitioning around medoids and also the Self organizing map technique in order to efficiently analyse and thus detect the sales fraud. The finding in our research, states that the self organizing maps and Hierarchical clustering provides good classification accuracy. These algorithms are strongly recommended in the field of fraud detection.

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A Novel Approach to Perform Analysis and Prediction on Breast Cancer Dataset using R

Cited by 17 publications

References 0 publications

Covid-19 Detection from Chest X-Ray Images Using Advanced Deep Learning Techniques

Covid-19 Detection from Chest X-Ray Images Using Advanced Deep Learning Techniques

Data Exploration on Overall Suicides Cases Registered Across India

Analyzing the performance of Various Fraud Detection Techniques

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