Deep learning (DL) techniques, more specifically Convolutional Neural Networks (CNNs), have become increasingly popular in advancing the field of data science and have had great successes in a wide array of applicatio...Deep learning (DL) techniques, more specifically Convolutional Neural Networks (CNNs), have become increasingly popular in advancing the field of data science and have had great successes in a wide array of applications including computer vision, speech, natural language processing, etc. However, the training process of CNNs is computationally intensive and has high computational cost, especially when the dataset is huge. To overcome these obstacles, this paper takes advantage of distributed frameworks and cloud computing to develop a parallel CNN algorithm. MapReduce is a scalable and fault-tolerant data processing tool that was developed to provide significant improvements in large-scale data-intensive applications in clusters. A MapReduce-based CNN (MCNN) is developed in this work to tackle the task of image classification. In addition, the proposed MCNN adopted the idea of adding dropout layers in the networks to tackle the overfitting problem. Close examination of the implementation of MCNN as well as how the proposed algorithm accelerates learning are discussed and demonstrated through experiments. Results reveal high classification accuracy and significant improvements in speedup, scaleup and sizeup compared to the standard algorithms.展开更多
10号染色体上磷酸酶和张力蛋白同源物(phosphatase and tensin-homolog deleted on chromosome 10,PTEN)是重要的抑癌基因,其突变可引发PTEN错构瘤肿瘤综合征(PTEN hamartoma tumor syndrome,PHTS),常被称为Cowden综合征,是较为罕见的...10号染色体上磷酸酶和张力蛋白同源物(phosphatase and tensin-homolog deleted on chromosome 10,PTEN)是重要的抑癌基因,其突变可引发PTEN错构瘤肿瘤综合征(PTEN hamartoma tumor syndrome,PHTS),常被称为Cowden综合征,是较为罕见的遗传性肿瘤综合征,其与早发性、多发性乳腺癌高度相关。本文报道3例PTEN基因突变相关单侧多中心乳腺癌及同时性、异时性双侧乳腺癌患者,并总结其临床表现、病理特征、诊治经验及随访情况,旨在为临床医生更好地诊治PTEN基因突变相关乳腺癌及Cowden综合征人群提供借鉴。展开更多
文摘Deep learning (DL) techniques, more specifically Convolutional Neural Networks (CNNs), have become increasingly popular in advancing the field of data science and have had great successes in a wide array of applications including computer vision, speech, natural language processing, etc. However, the training process of CNNs is computationally intensive and has high computational cost, especially when the dataset is huge. To overcome these obstacles, this paper takes advantage of distributed frameworks and cloud computing to develop a parallel CNN algorithm. MapReduce is a scalable and fault-tolerant data processing tool that was developed to provide significant improvements in large-scale data-intensive applications in clusters. A MapReduce-based CNN (MCNN) is developed in this work to tackle the task of image classification. In addition, the proposed MCNN adopted the idea of adding dropout layers in the networks to tackle the overfitting problem. Close examination of the implementation of MCNN as well as how the proposed algorithm accelerates learning are discussed and demonstrated through experiments. Results reveal high classification accuracy and significant improvements in speedup, scaleup and sizeup compared to the standard algorithms.
文摘10号染色体上磷酸酶和张力蛋白同源物(phosphatase and tensin-homolog deleted on chromosome 10,PTEN)是重要的抑癌基因,其突变可引发PTEN错构瘤肿瘤综合征(PTEN hamartoma tumor syndrome,PHTS),常被称为Cowden综合征,是较为罕见的遗传性肿瘤综合征,其与早发性、多发性乳腺癌高度相关。本文报道3例PTEN基因突变相关单侧多中心乳腺癌及同时性、异时性双侧乳腺癌患者,并总结其临床表现、病理特征、诊治经验及随访情况,旨在为临床医生更好地诊治PTEN基因突变相关乳腺癌及Cowden综合征人群提供借鉴。
