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"This third volume of the Springer series discussing pediatric cancer focuses on diagnosing, treating, and assessing the future course of malignant brain neoplasms in children. In addition to a general introduction to the principals involved, the material includes vital research in molecular genetics, a major contribution to the molecular characterization of solid tumors, which will define new biomarkers of the disease and identify molecular pathways. The volume includes presentations of present and future therapies. The volume also explains AT/RT’s dissemination to the cerebral fluid, the molecular mechanisms underlying the progression of medulloblastoma, and the importance of gamma knife radiosurgery during multimodality management of medulloblastoma/PNET tumors. Other topics discussed include using magnetic resonance imaging for diagnosing retinoblastoma, and mapping the effects of radiotherapy in low-grade glioma in children. Information on alterations in cell-cycle regulators that are influenced by tumor suppressor genes and oncogenes is detailed. Contributors provide recommendations concerning non-narcotic analgesic routines for children recovering from cranial and spinal surgery. "

"Cancer can affect people of all ages, and approximately one in three people are estimated to be diagnosed with cancer during their lifetime. Extensive research is being undertaken by many different institutions to explore potential new therapeutics, and biomaterials technology is now being developed to target, treat and prevent cancer. This unique book discusses the role and potential of biomaterials in treating this prevalent disease.The first part of the book discusses the fundamentals of biomaterials for cancer therapeutics. Chapters in part two discuss synthetic vaccines, proteins and polymers for cancer therapeutics. Part three focusses on theranosis and drug delivery systems, whilst the final set of chapters look at biomaterial therapies and cancer cell interaction.This extensive book provides a complete overview of the latest research into the potential of biomaterials for the diagnosis, therapy and prevention of cancer. Biomaterials for cancer therapeutics is an essential text for academics, scientists and researchers within the biomedical industry, and will also be of interest to clinicians with a research interest in cancer therapies and biomaterials."

"Penerimaan seseorang yang terdiagnosis kanker payudara akan memberikan pengaruh terhadap komitmennya dalam menjalani pengobatan, yang selanjutnya akan memberikan pengaruh terhadap kualitas hidup pasien tersebut. Penelitian ini bertujuan untuk mengidentifikasi faktor yang berpengaruh terhadap tingkat penerimaan pasien. Desain penelitian yang digunakan adalah Cross Sectional dengan 180 orang responden. Analisis data yang digunakan adalah regresi logistik. Instrumen penelitian yang digunakan untuk melihat penerimaan adalah Acceptance Of Illness Scale (AIS). Hasil penelitian menunjukkan bahwa penerimaan pasien di RSUD Provinsi Sumatra Barat 60,6% adalah baik. Sedangkan faktor yang mempengaruhi kualitas hidup pasien adalah: Usia (p = 0,006), pendidikan (p = 0,902) pekerjaan (p = 0,006), lama menderita (p = 001), metastase (p=0,003) jumlah pengobatan (p =0,000) dukungan keluarga (p = 0,014), Spiritual (p=0,001) mekanisme koping (p=0,038). Hasil analisis multivariat didapatkan faktor yang dominan mempengaruhi tahap penerimaan adalah spiritual. Kesimpulan: Penerimaan pasien dapat ditingkatkan dengan mengoptimalkan faktor-faktor yang dimiliki oleh penderita kanker payudara. Saran: Penelitian lebih lanjut tentang variabel pekerjaan lebih dijelaskan berdasarkan status profesional.

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Acceptance of a person diagnosed with breast cancer will have an effect on his commitment to undergoing treatment, which in turn will affect the quality of life of the patient. This study aims to identify factors that affect the level of patient acceptance. The research design used was Cross Sectional with 180 respondents. Data analysis used is logistic regression. The research instrument used to view acceptance is Acceptance Of Illness Scale (AIS). The results showed that the acceptance of patients in West Sumatra Province Hospital 60.6% was good. While the factors that influence the quality of life of the patient are: Age (p = 0,006), education (p = 0,902) job (p = 0,006), long suffering (p = 001), metastase (p = 0,003) family support (p = 0.014), Spiritual (p = 0.001) coping mechanism (p = 0.038). The result of multivariate analysis found that the dominant factor influencing the acceptance stage is spiritual. Conclusion: Acceptance of patients can be improved by optimizing the factors that are owned by patients with breast cancer. Suggestions: Further research on job variables is more described by professional status."

"Diagnosis kanker payudara umum menggunakan data morfologi dan infomasi klinis. Akan tetapi diagnosis kanker yang akurat dibutuhkan untuk menangani dan terapi yang tepat. Deteksi ekspresi gen merupakan cara yang dapat digunakan untuk menganalisis kanker hingga tingkat molekuler. Microarray adalah teknologi yang memungkinkan analisis ribuan ekspresi gen dalam waktu yang bersamaan. Pembelajaran mesin dapat digunakan untuk menganalisis pola pada microarray dataset. Model pembelajan dengan deep learning, seperti deep stacking network DSN diperlukan untuk data yang kompleks seperti pada microarray. DSN pertama kali diusulkan untuk mengatasi kekurangan dari deep learning pada umumnya. Selain itu dikarenakan tingginya dimensi data microarray, sebelum melalui proses pembelajaran diperlukan reduksi dimensi pada data microarray. Reduksi data menggunakan gene shaving, dimana data akan dikelompokan menjadi beberapa cluster dan juga dengan PCA. Selanjutnya data yang sudah direduksi melalui proses pembelajaran pada model DSN yang terdiri dari 2-layer, 3-layer dan 4-layer dengan laju pembelajaran 0.01, 0.1 dan 1.0. Parameter yang diukur adalah nilai akurasi, mean square error MSE dan waktu eksekusi, dimana nilai terbaik didapatkan pada DSN 2-layer dengan laju pembelajaran 1.0 pada data hasil reduksi PCA.

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The diagnosis of breast cancer uses morphological data and clinical information. However, an accurate cancer diagnosis is necessary for the proper treatment. Gene expression detection is a way that can be used to analyze cancer to the molecular level. Microarray is a technology that allows the analysis of thousands of gene expression at the same time. Machine learning can be used to analyze patterns in the microarray dataset. Machine learning with deep architecture deep learning, such as deep stacking learning DSN, is needed for complex data such as microarray. DSN was proposed to overcome the shortage of deep learning. In addition, due to the high dimension of microarray data, dimension reduction in microarray data is required before going through the learning process. Data reduction uses gene shaving, where data will be grouped into clusters and also PCA. Clusters found through the process of gene shaving is a cluster that carries important genetic information in cancer cells so that the gene can represent all data. Furthermore, the data has been reduced going through the learning process on the DSN model consisting of 2 layer, 3 layer and 4 layer with the learning rate of 0.01, 0.1 and 1.0. The parameters measured are the accuracy, mean square error MSE and execution time, which the best value is obtained on 2 layer DSN with learning rate 1.0 on data from the reduction of PCA."

"The book is the first one published exclusively on the field of nutritional epidemiology of breast cancer. It summarizes the currently existing knowledge, with an updated and comprehensive international bibliography (~ 1.000 references). The authors also performed a review on the epidemiological studies on nutrition and breast cancer carried out in Uruguay between 1994 and 2011, which allowed exploring and identifying the main risk and protective factors for the disease in this high-risk country. "

"This book is the one of the few textbooks that summarizes the latest information dated to inflammatory breast cancer. The uniqueness of this book is that it has summarized the latest molecular and mechanistic findings, which may lead to novel diagnostic tool or therapeutic approach to fight this deadly disease."

"Nyeri kanker dapat mempengaruhi kualitas hidup pasien. Tehnik distraksi yang cukup sederhana dan efektif untuk mengatasi nyeri kanker yakni dengan kombinasi terapi musik dan visual art therapy. Penelitian ini bertujuan untuk mengetahui pengaruh kombinasi terapi musik dan visual art therapy. Penelitian ini menggunakan desain quasi experimen dengan melibatkan 34 responden yang dipilih secara purposive sampling. Hasil penelitian ini menunjukkan terdapat perbedaan yang signifikan tingkat nyeri setelah perlakuan antara kelompok yang hanya mendapat terapi standar analgesik dengan kelompok yang mendapat kombinasi terapi musik dan visual art therapy dengan p-velue = 0,008 p 0,05. Berdasarkan hasil penelitian dapat disimpulkan bahwa kombinasi terapi musik dan visual art therapy lebih efektif untuk menurunkan nyeri pada pasien kanker payudara dibandingkan terapi standar analgesik saja. Hasil penelitian ini dapat menjadi salah satu rekomendasi intervensi untuk mengurangi nyeri pada pasien kanker payudara serta mendorong kemandirian dalam peran autonomi perawat.

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The pain caused by cancer may affect the patient rsquo s quality of life. The distraction technique is quite simple and effective to overcome the pain caused by cancer, i.e. with the combined therapy of music and visual art therapy. The objective of this research was to identify the effects of combined therapy of music and visual art therapy. This research used the quasi experiment design involving 34 respondents selected by way of purposive sampling.

The results of this research indicated that there was a significant difference in the pain level after the treatment between the group only receiving the standard analgesic therapy and the group receiving the combined therapy of music and visual art therapy with the p value 0.008 p0.05.

Based on the results of research, it may be concluded that the combined therapy of music and visual art therapy is more effective to reduce pain in breast cancer patients than the standard analgesic therapy only. The results of this research may become one of the interventional recommendation to reduce pain in breast cancer patients as well as encouraging independence in the autonomous role of nurses."