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https://www.readbyqxmd.com/read/29040911/a-deep-learning-model-integrating-fcnns-and-crfs-for-brain-tumor-segmentation
#1
Xiaomei Zhao, Yihong Wu, Guidong Song, Zhenye Li, Yazhuo Zhang, Yong Fan
Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices...
October 5, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/29040639/the-medical-science-dmz-a-network-design-pattern-for-data-intensive-medical-science
#2
Sean Peisert, Eli Dart, William Barnett, Edward Balas, James Cuff, Robert L Grossman, Ari Berman, Anurag Shankar, Brian Tierney
Objective: We describe a detailed solution for maintaining high-capacity, data-intensive network flows (eg, 10, 40, 100 Gbps+) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods: High-end networking, packet-filter firewalls, network intrusion-detection systems. Results: We describe a "Medical Science DMZ" concept as an option for secure, high-volume transport of large, sensitive datasets between research institutions over national research networks, and give 3 detailed descriptions of implemented Medical Science DMZs...
October 6, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/29040554/frailty-syndrome-an-emerging-clinical-problem-in-the-everyday-management-of-clinical-arrhythmias-the-results-of-the-european-heart-rhythm-association-survey
#3
Stefano Fumagalli, Tatjana S Potpara, Torben Bjerregaard Larsen, Kristina H Haugaa, Dan Dobreanu, Alessandro Proclemer, Nikolaos Dagres
The age of patients presenting with complex arrhythmias is increasing. Frailty is a multifaceted syndrome characterized by an increased vulnerability to stressors and a decreased ability to maintain homeostasis. The prevalence of frailty is associated with age. The aims of this European Heart Rhythm Association (EHRA) EP Wire survey were to evaluate the proportion of patients with frailty and its influence on the clinical management of arrhythmias. A total of 41 centres-members of the EHRA Electrophysiology Research Network-in 14 European countries completed the web-based questionnaire in June 2017...
October 10, 2017: Europace: European Pacing, Arrhythmias, and Cardiac Electrophysiology
https://www.readbyqxmd.com/read/29036877/a-hybrid-cnn-feature-model-for-pulmonary-nodule-malignancy-risk-differentiation
#4
Huafeng Wang, Tingting Zhao, Lihong Connie Li, Haixia Pan, Wanquan Liu, Haoqi Gao, Fangfang Han, Yuehai Wang, YiFang Qi, Zhengrong Liang
The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features, we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI)...
October 10, 2017: Journal of X-ray Science and Technology
https://www.readbyqxmd.com/read/29036627/using-uncertainty-to-link-and-rank-evidence-from-biomedical-literature-for-model-curation
#5
Chrysoula Zerva, Riza Batista-Navarro, Philip Day, Sophia Ananiadou
Motivation: In recent years, there has been great progress in the field of automated curation of biomedical networks and models, aided by text mining methods that provide evidence from literature. Such methods must not only extract snippets of text that relate to model interactions, but also be able to contextualize the evidence and provide additional confidence scores for the interaction in question. Although various approaches calculating confidence scores have focused primarily on the quality of the extracted information, there has been little work on exploring the textual uncertainty conveyed by the author...
July 24, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29036404/the-value-of-prior-knowledge-in-machine-learning-of-complex-network-systems
#6
Dana Ferranti, David Krane, David Craft
Motivation: Our overall goal is to develop machine-learning approaches based on genomics and other relevant accessible information for use in predicting how a patient will respond to a given proposed drug or treatment. Given the complexity of this problem, we begin by developing, testing and analyzing learning methods using data from simulated systems, which allows us access to a known ground truth. We examine the benefits of using prior system knowledge and investigate how learning accuracy depends on various system parameters as well as the amount of training data available...
July 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29035873/multi-task-transfer-learning-deep-convolutional-neural-network-application-to-computer-aided-diagnosis-of-breast-cancer-on-mammograms
#7
Ravi K Samala, Heang-Ping Chan, Lubomir M Hadjiiski, Mark A Helvie, Kenny Cha, Caleb Richter
Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aims of translating the 'knowledge' learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses...
October 16, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29034482/deep-reinforcement-learning-for-automated-radiation-adaptation-in-lung-cancer
#8
Huan-Hsin Tseng, Yi Luo, Sunan Cui, Jen-Tzung Chien, Randall K Ten Haken, Issam El Naqa
PURPOSE: To investigate deep reinforcement learning (DRL) based on historical treatment plans for developing automated radiation adaptation protocols for non-small cell lung cancer (NSCLC) patients that aim to maximize tumor local control at reduced rates of radiation pneumonitis grade 2 (RP2). METHODS: In a retrospective population of 114 NSCLC patients who received radiotherapy, a 3-component neural networks framework was developed for deep reinforcement learning (DRL) of dose fractionation adaptation...
October 16, 2017: Medical Physics
https://www.readbyqxmd.com/read/29033978/integrative-analysis-of-transcription-factor-combinatorial-interactions-using-a-bayesian-tensor-factorization-approach
#9
Yusen Ye, Lin Gao, Shihua Zhang
Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network...
2017: Frontiers in Genetics
https://www.readbyqxmd.com/read/29033850/designing-dietary-recommendations-using-system-level-interactomics-analysis-and-network-based-inference
#10
Tingting Zheng, Yueqiong Ni, Jun Li, Billy K C Chow, Gianni Panagiotou
Background: A range of computational methods that rely on the analysis of genome-wide expression datasets have been developed and successfully used for drug repositioning. The success of these methods is based on the hypothesis that introducing a factor (in this case, a drug molecule) that could reverse the disease gene expression signature will lead to a therapeutic effect. However, it has also been shown that globally reversing the disease expression signature is not a prerequisite for drug activity. On the other hand, the basic idea of significant anti-correlation in expression profiles could have great value for establishing diet-disease associations and could provide new insights into the role of dietary interventions in disease...
2017: Frontiers in Physiology
https://www.readbyqxmd.com/read/29033691/identification-of-genes-and-pathways-potentially-related-to-phf20-by-gene-expression-profile-analysis-of-glioblastoma-u87-cell-line
#11
Tianlong Liu, Tiejun Zhang, Feng Zhou, Jitao Wang, Xiaohu Zhai, Nan Mu, Jongsun Park, Minna Liu, Wenxing Liu, Peijin Shang, Yi Ding, Aidong Wen, Yuwen Li
BACKGROUND: Glioblastoma is the most common and aggressive brain tumor associated with a poor prognosis. Plant homeodomain finger protein 20 (PHF20) is highly expressed in primary human gliomas and its expression is associated with tumor grade. However, the molecular mechanism by which PHF20 regulates glioblastoma remains poorly understood. METHODS: Genome wide gene expression analysis was performed to identify differentially expressed genes (DEGs) in U87 cells with PHF20 gene knockdown...
2017: Cancer Cell International
https://www.readbyqxmd.com/read/29033189/mir-375-a-prospective-regulator-in-medullary-thyroid-cancer-based-on-microarray-data-and-bioinformatics-analyses
#12
Lin Shi, Shi-Mei Zhao, Yu Luo, An-Wen Zhang, Li-Hua Wei, Zheng-Yi Xie, Yuan-Yuan Li, Wei Ma
BACKGROUND: This research aims to investigate the prospective molecular mechanism of miR-375 in Medullary Thyroid Cancer (MTC). MATERIAL AND METHODS: The expression level of miR-375 in MTC was explored with microarray data from Gene Expression Omnibus (GEO). To gather the putative target genes of miR-375, we selected eligible datasets in GEO, in which antagomir-375 and premir-375 were transfected to provide the miR-375-related genes. Subsequently, we attained the intersection of the results of GEO microarray data and 12 online target genes prediction database as the prospective target genes...
September 27, 2017: Pathology, Research and Practice
https://www.readbyqxmd.com/read/29032924/epidemiology-of-rare-cancers-and-inequalities-in-oncologic-outcomes
#13
G Gatta, A Trama, R Capocaccia
Rare cancers epidemiology is better known compared to the other rare diseases. Thanks to the long history of the European population-based cancer registries and to the EUROCARE huge database, the burden of rare cancers has been estimated the European (EU28) population. A considerable fraction of all cancers is represented by rare cancers (24%). They are a heterogeneous group of diseases, but they share similar problems: uncertainty of diagnosis, lack of therapies, poor research opportunities, difficulties in clinical trials, lack of expertise and of centres of reference...
September 19, 2017: European Journal of Surgical Oncology
https://www.readbyqxmd.com/read/29032717/bet-inhibitors-in-metastatic-prostate-cancer-therapeutic-implications-and-rational-drug-combinations
#14
Mark C Markowski, Angelo M De Marzo, Emmanuel S Antonarakis
The bromodomain and extra-terminal (BET) family of proteins are epigenetic readers of acetylated histones regulating a vast network of protein expression across many different cancers. Therapeutic targeting of BET is an attractive area of clinical development for metastatic castration-resistant prostate cancer (mCRPC), particularly due to its putative effect on c-MYC expression and its interaction with the androgen receptor (AR). Areas Covered: We speculate that a combination approach using BET inhibition with other targeted therapies may be required to improve the therapeutic index of BET inhibition in the management of prostate cancer...
October 16, 2017: Expert Opinion on Investigational Drugs
https://www.readbyqxmd.com/read/29032608/microrna-profiling-reveals-dysregulated-micrornas-and-their-target-gene-regulatory-networks-in-cemento-ossifying-fibroma
#15
Thaís Dos Santos Fontes Pereira, João Artur Ricieri Brito, André Luiz Sena Guimarães, Carolina Cavaliéri Gomes, Júlio Cesar Tanos de Lacerda, Wagner Henriques de Castro, Roney Santos Coimbra, Marina Gonçalves Diniz, Ricardo Santiago Gomez
BACKGROUND: Cemento-ossifying fibroma (COF) is a benign fibro-osseous neoplasm of uncertain pathogenesis and its treatment results morbidity. MicroRNAs (miRNA) are small non-coding RNAs that regulate gene expression and may represent therapeutic targets. The purpose of the study was to generate a comprehensive miRNA profile of COF compared to normal bone. Additionally, the most relevant pathways and target genes of differentially expressed miRNA were investigated by in silico analysis...
October 15, 2017: Journal of Oral Pathology & Medicine
https://www.readbyqxmd.com/read/29032296/most-gleason-8-biopsies-are-downgraded-on-prostatectomy-does-4-4-7
#16
Ted Gansler, Stacey Fedewa, Robert Qi, Chun Chieh Lin, Ahmedin Jemal, Judd W Moul
PURPOSE: Non-representative biopsy sampling of prostate cancers with a biopsy Gleason score of 8 can adversely influence decisions regarding androgen deprivation among men receiving primary radiation therapy. The frequency of and factors associated with downgrading of Gleason 8 biopsies at prostatectomy are not well known. MATERIALS AND METHODS: Records from the National Cancer Database (a hospital-based registry in the United States) of 72,556 men with prostate cancer diagnosed 2010-2013, including 5,474 with Gleason 8 biopsies and no other high progression-risk criteria (per National Comprehensive Cancer Network guidelines)...
October 11, 2017: Journal of Urology
https://www.readbyqxmd.com/read/29032203/construction-of-artificial-human-peritoneal-tissue-by-cell-accumulation-technique-and-its-application-for-visualizing-morphological-dynamics-of-cancer-peritoneal-metastasis
#17
Yoshiya Asano, Tadashi Odagiri, Hiroe Oikiri, Michiya Matsusaki, Mitsuru Akashi, Hiroshi Shimoda
Human peritoneum is composed of mesothelial monolayer and stromal tissue containing microvasculature. Dissemination and infiltration of cancer cells to the peritoneum result in cancer peritoneal metastasis which is an important prognostic factor of intraperitoneal or intrapelvic carcinoma. To elucidate an initial metastatic mechanism of cancer cells, in vitro human peritoneal models are demanded. In this study, we created a three-dimensional artificial human peritoneal tissue (AHPT) harboring the blood or lymphatic vascular network by cell-accumulation technique...
October 11, 2017: Biochemical and Biophysical Research Communications
https://www.readbyqxmd.com/read/29032073/a-compendium-of-co-regulated-protein-complexes-in-breast-cancer-reveals-collateral-loss-events
#18
Colm J Ryan, Susan Kennedy, Ilirjana Bajrami, David Matallanas, Christopher J Lord
Protein complexes are responsible for the bulk of activities within the cell, but how their behavior and abundance varies across tumors remains poorly understood. By combining proteomic profiles of breast tumors with a large-scale protein-protein interaction network, we have identified a set of 285 high-confidence protein complexes whose subunits have highly correlated protein abundance across tumor samples. We used this set to identify complexes that are reproducibly under- or overexpressed in specific breast cancer subtypes...
October 10, 2017: Cell Systems
https://www.readbyqxmd.com/read/29031853/co-expression-modules-construction-by-wgcna-and-identify-potential-prognostic-markers-of-uveal-melanoma
#19
Qi Wan, Jing Tang, Yu Han, Dan Wang
Uveal melanoma is an aggressive cancer which has a high percentage recurrence and with a worse prognosis. Identify the potential prognostic markers of uveal melanoma may provide information for early detection of recurrence and treatment. RNA sequence data of uveal melanoma and patient clinic traits were obtained from The Cancer Genome Atlas (TCGA) database. Co-expression modules were built by weighted gene co -expression network analysis (WGCNA) and applied to investigate the relationship underlying modules and clinic traits...
October 12, 2017: Experimental Eye Research
https://www.readbyqxmd.com/read/29031778/extended-adjuvant-aromatase-inhibition-after-sequential-endocrine-therapy-data-a-randomised-phase-3-trial
#20
Vivianne C G Tjan-Heijnen, Irene E G van Hellemond, Petronella G M Peer, Astrid C P Swinkels, Carolien H Smorenburg, Maurice J C van der Sangen, Judith R Kroep, Hiltje De Graaf, Aafke H Honkoop, Frans L G Erdkamp, Franchette W P J van den Berkmortel, Maaike de Boer, Wilfred K de Roos, Sabine C Linn, Alexander L T Imholz, Caroline M Seynaeve
BACKGROUND: The effect of extended adjuvant aromatase inhibition in hormone receptor-positive breast cancer after sequential endocrine therapy of tamoxifen followed by an aromatase inhibitor for a 5-year treatment period still needs clarification. To address this issue, we began the DATA study to assess different durations of anastrozole therapy after tamoxifen. METHODS: DATA was a prospective, randomised, open-label, multicentre, phase 3 study done in 79 hospitals in the Netherlands...
October 11, 2017: Lancet Oncology
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