scholarly journals Logistic Broken Adaptive Ridge Procedure for Colon Cancer Data Analysis

2019 ◽  
pp. 1-5
Author(s):  
Hong Yin ◽  
Hong Yin ◽  
Liangzhen Lei ◽  
Suyun Zhao
Keyword(s):  
Colon Cancer ◽  
Cancer Detection ◽  
Training Data ◽  
Cancer Data ◽  
The People ◽  
The World ◽  
Testing Data ◽  
Causes And Risk Factors ◽  
Or Genes ◽  
Colon Cancer Data

Background: Colon cancer is the leading cause of cancer-related deaths in the world in both man and women. Knowing the causes and risk factors for colon cancer can help you understanding the importance of routine screening for colon cancer, as well as learn if you are one of the people who should begin screening at the earlier age. Due to the limitation of clinical diagnose, management and treatment outcomes, it is of great necessity to develop effective methods for colon cancer detection and prediction especially cDNA Microarrays and high- density oligonucleotide chips are increasingly used in cancer research. Methods: Here we propose a novel logistic broken adaptive ridge procedure to address the problem of colon cancer results prediction through selecting effective few variables or genes from 2000 candidate genes. Results: In total 62 cases with 40 colon cancer patients and 22 healthy patients were included in our analysis. Each case consists of 2000 genes which challenged all the competitive method. From the results, we are so surprised that our proposed method outperforms the classical variable selection approaches in error rate of training data and extra testing data. Conclusions: Logistic adaptive ridge procedure is very effective for colon cancer predictions, either in terms of prognosis or diagnose. It may benefit patients by guiding therapeutic options. We hope it will contribute to the wider biology and related communities.

scholarly journals Cancer Detection based on Microarray Data Classification Using FLNN and Hybrid Feature Selection

2021 ◽  
Vol 5 (4) ◽  
pp. 794-801
Author(s):  
Ghozy Ghulamul Afif ◽  
Adiwijaya ◽  
Widi Astuti
Keyword(s):  
Cancer Detection ◽  
Information Gain ◽  
Test Results ◽  
Cancer Data ◽  
Dimensional Reduction Method ◽  
The World ◽  
Diagnosis Of Cancer ◽  
Microarray Dna ◽  
Combining Information ◽  
Colon Cancer Data

Cancer is one of the second deadliest diseases in the world after heart disease. Citing from the WHO's report on cancer, in 2018 there were around 18.1 million cases of cancer in the world with a total of 9.6 million deaths. Now that bioinformatics technology is growing and based on WHO’s report on cancer, an early detection is needed where bioinformatics technology can be used to diagnose cancer and to help to reduce the number of deaths from cancer by immediately treating the person. Microarray DNA data as one of the bioinformatics technology is becoming popular for use in the analysis and diagnosis of cancer in the medical world. Microarray DNA data has a very large number of genes, so a dimensional reduction method is needed to reduce the use of features for the classification process by selecting the most influential features. After the most influential features are selected, these features are going to be used for the classification and predict whether a person has cancer or not. In this research, hybridization is carried out by combining Information Gain as a filtering method and Genetic Algorithm as a wrapping method to reduce dimensions, and lastly FLNN as a classification method. The test results get colon cancer data to get the highest accuracy value of 90.26%, breast cancer by 85.63%, lung cancer and ovarian cancer by 100%, and prostate cancer by 94.10%.

Classification of Rat FTIR Colon Cancer Data Using Wavelets and BPNN

2009 ◽  
Vol 27 (5) ◽  
pp. 911-914 ◽  
Author(s):  
Cungui CHENG ◽  
Wei XIONG ◽  
Yumei TIAN
Keyword(s):  
Colon Cancer ◽  
Cancer Data ◽  
Colon Cancer Data

Identifikasi Warna Kerabang Telur Ayam Ras Menggunakan Jaringan Syaraf Tiruan

2018 ◽  
Vol 6 (2) ◽  
pp. 189-200
Author(s):  
Iman Budi Darmawan ◽  
Maimunah Maimunah ◽  
Retno Nugroho Whidiasih
Keyword(s):  
Food Source ◽  
Training Data ◽  
Nutritional Content ◽  
The People ◽  
Testing Data ◽  
Color Identification ◽  
Hidden Layer ◽  
Chicken Eggs ◽  
Backpropagation Artificial Neural Network ◽  
Better Than

Abstract   Eggs are a food source of animal protein that is cheap and easy to get by the people of Indonesia. Eggs have a complete nutritional content ranging from protein, fat, vitamins and minerals. This study aims to identify the color of broiler eggshell to dark brown, brown, and light brown, it shows that dark brown chicken eggs are better than brown and light brown. The estimator variable used is RGB (red, green, blue), extraction from the egg image taken using a 20 megapixel DSLR camera. The data used is 90 egg images. Training data amounted to 72 data and testing data totaling 18 data. Color identification of eggshells using backpropagation artificial neural network with the penduga red, green, blue parameters of the egg image, the most optimal weight obtained at 59th epoch at 03 seconds with neurons 2 in the hidden layer, with an MSE value of 0.160 and a success rate of 72%.   Keywords: backpropagation, identification, race chicken eggs, RGB, shell color.   Abstrak   Telur merupakan makanan sumber protein hewani yang murah dan mudah untuk didapatkan oleh masyarakat Indonesia. Telur memiliki kandungan gizi yang lengkap mulai dari protein, lemak, vitamin, dan mineral. Penelitian ini bertujuan untuk mengidentifikasi warna kerabang telur ayam ras menjadi warna coklat tua, coklat, dan coklat muda, hal tersebut menunjukkan bahwa telur ayam dengan warna coklat tua lebih baik dibandingkan dengan warna coklat dan coklat muda. Variabel penduga yang digunakan adalah rgb (red, green, blue), ekstraksi dari citra telur yang diambil menggunakan kamera DSLR 20 megapiksel. Data yang digunakan berjumlah 90 citra telur. Data training berjumlah 72 data dan data testing berjumlah 18 data. Identifikasi warna kerabang telur menggunakan jaringan syaraf tiruan backpropagation dengan parameter penduga red, green, blue dari citra telur, bobot yang paling optimal didapatkan pada epoch ke 59 di detik ke 03 dengan neuron 2 pada lapisan tersembunyi, dengan nilai MSE sebesar  0.160 dan tingkat keberhasilan sebesar 72%.   Kata kunci: backpropagation, identifikasi, RGB, telur ayam ras, warna kerabang.

Comparison of conventional access routes for right hemicolectomy in colon cancer—data from the DGAV StuDoQ registry

2018 ◽  
Vol 34 (1) ◽  
pp. 161-167
Author(s):  
Christian Jurowich ◽  
Sven Lichthardt ◽  
Niels Matthes ◽  
Caroline Kastner ◽  
Imme Haubitz ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Right Hemicolectomy ◽  
Cancer Data ◽  
Colon Cancer Data
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