Haque MR, Islam MM, Iqbal H, Reza MS, Hasan MK. IEEE Region 10 Humanitarian Technology Conference (R10-HTC), Dhaka, 2017, pp. Prediction of breast cancer using support vector machine and K-Nearest neighbors. Predictive data mining models for novel coronavirus (COVID-19) infected patients’ recovery. Muhammad LJ, Islam MM, Usman SS, Ayon SI. Coronary artery heart disease prediction: a comparative study of computational intelligence techniques. Interobserver variability of ultrasound elastography and the ultrasound BI-RADS lexicon of breast lesions. Park CS, Kim SH, Jung NY, Choi JJ, Kang BJ, Jung HS. Dynamic-enhanced MRI predicts metastatic potential of invasive ductal breast cancer. Nagashima T, Suzuki M, Yagata H, Hashimoto H, Shishikura T, Imanaka N, Miyazaki M. Probabilistic neural network for breast cancer classification. Molecular imaging using PET for breast cancer. Kurihara H, Shimizu C, Miyakita Y, Yoshida M, Hamada A, Kanayama Y, Tamura K. Diagnostic accuracy of contrast-enhanced spectral mammography in comparison to conventional full-field digital mammography in a population of women with dense breasts. Mori M, Akashi-Tanaka S, Suzuki S, Daniels MI, Watanabe C, Hirose M, Nakamura S. 2018 286(3):800–9.īreast Cancer: Statistics, Approved by the Cancer.Net Editorial Board, 04/2017. Methodologic guide for evaluating clinical performance and effect of artificial intelligence technology for medical diagnosis and prediction. The results reveal that the ANNs obtained the highest accuracy, precision, and F1 score of 98.57%, 97.82%, and 0.9890, respectively, whereas 97.14%, 95.65%, and 0.9777 accuracy, precision, and F1 score are obtained by SVM, respectively. Additionally, these techniques were appraised on precision–recall area under curve and receiver operating characteristic curve. The performance of the study is measured with respect to accuracy, sensitivity, specificity, precision, negative predictive value, false-negative rate, false-positive rate, F1 score, and Matthews Correlation Coefficient. The Wisconsin Breast Cancer dataset is obtained from a prominent machine learning database named UCI machine learning database. In this paper, we compare five supervised machine learning techniques named support vector machine (SVM), K-nearest neighbors, random forests, artificial neural networks (ANNs) and logistic regression. An automatic disease detection system aids medical staffs in disease diagnosis and offers reliable, effective, and rapid response as well as decreases the risk of death. Breast cancer is the second most severe cancer among all of the cancers already unveiled. With the rapid population growth, the risk of death incurred by breast cancer is rising exponentially. Both Red Bull and Mercedes will continue a close fight during the last few races of 2021," concludes Jaki.Early detection of disease has become a crucial problem due to rapid population growth in medical research in recent times. Whoever does the best homework during the team simulation preparations before the Saudi Arabia Grand Prix will have the upper hand. "The Saudi Arabia race is up for the taking. Bottas remains inconsistent at the best of times, fluctuating between excellent and nowhere," says Jaki. He agrees that team Red Bull will dominate Brazil: "However, with Perez's performance improvement in the last few races, he will continue to give Mercedes and Hamilton even bigger headaches. Jaki predicts the Brazilian Grand Prix placings to be Verstappen, Perez, Hamilton. Ian says anything can happen at the Saudi Arabia Grand Prix due to the new track, but he believes Red Bull has a better chance than the rest of the teams, as it is currently the "fiercer" team: "The results will remain more or less the same for me in Saudi Arabia if they race 'clean' in the upcoming Brazil Grand Prix this Sunday." The Red Bull team have the upper hand after last weekend's Mexican Grand Prix, and the upcoming Brazil race will suit the team," says Ian Scheckter. "I predict the finishing line for the upcoming Brazilian Grand Prix to be Verstappen, Hamilton, Bottas, Perez. Getty Images Photo by Dario Oliveira/Anadolu Agency
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