Cancer Detection

Background: Cancer detection using sniffer dogs is a potential technology for clinical use and research. Our study sought to determine whether dogs could be trained to discriminate the odour of urine from men with prostate cancer from controls, using rigorous testing procedures and well-defined samples from a major research hospital.

The diagnosis of cancer involves the analysis of tissue and cytology specimens obtained through several surgical procedures, including surgical biopsy, endoscopic biopsy, core or aspiration needle biopsy, venipuncture, spinal tap, pleural or ascitic tap, scraping of tissue surfaces and collection of exfoliative cells from urine and sputum. A tumor marker is one which can be used at an early stages of the cancer which indicates the likely presence of cancer or that provides the likely information about the future behavior of a cancer.

Naturally, cells in human body grow and divide in a controlled way to produce more cells to maintain health. Cancer affects human body when abnormal cells divide without control and becomes able to invade other tissues. The genetic material (DNA) of these cells becomes damaged or changed that affects normal cell growth and division. Early diagnosis is of considerable significance of the physician's skills conducted based on their knowledge and experience yet an error might occur. A range of therapies have been provided by researchers already. Use of various Artificial Intelligence methods for medical diagnosis of diseases has recently become widespread. These intelligent systems help physicians as a diagnosis assistant. Now, various Artificial Neural Network, Rough Set, Decision Tree, Bayesian Network are very popular for this purpose. In this paper, Multi layer Feed Forward Neural Network was used to detect cancer from Microarray Data and UCI Machine Learning Data. Back Propagation Rule was used for training the model. Throughout this paper, two types of validations were performed: cross validation and new case testing for above two datasets with different combination of hidden layers and corresponding nodes. It was found that, NN model can classify the data with very good accuracy and this will lead to automated medical diagnosis system for the particular disease.

Dear Sir/Madam

We are currently hosting the Oncologist & Diagnostics Conference  which is going to be organized during August 28-30, 2017 Brussels, Belgium. With great pride and honour, we would like to invite you to participate in Oncologist & Diagnostics Conference in Brussels, Belgium

Kindly let me know about you interest toward participation as a Keynote, Speaker, Poster presentation, E-Poster and Video Presentation, delegate.
Kindly find the attached file for conference details

Kindly contact us for any sort of further assistance.
We sincerely hope that you will honour us by accepting our invitation

Regards
Celina Crystal
Manager of oncology and conferences
P 702 508 5200 Ext 8033
#cancerdiagnostics@cancersummit.org

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ConferenceSeries Ltd invites all the participants across the globe to attend the Oncologist & Diagnostics Conference slated on August 28-30, 2017 at Brussels, Belgium.

Cancer Diagnostics 2017 directs towards addressing main issues as well as future strategies of Cancer. This is going to be the largest and most promising international conference where the program includes Clinical Oncologists, Registered Nurses, Nurse practitioners and the entire medical team involved in patient care, researchers, professional, early career individuals and patient advocates who wish to learn principles of tumor immunology and immunotherapy well as decision makers will come to discuss and debate on various aspects of the challenges, risks and investment opportunities throughout the complete information of Cancers. Cancer Diagnostics 2017 will also provide the three days of discussions on methods and strategies related to management and quality improvement of Diagnostics device developing and Cancer Research and as well as to explore the new ideas and concepts on global scale and the topics include lung cancer, breast cancer, bone cancer, leukemia, blood cancer, cervical cancer, colon-rectum cancer, pediatric cancer, surgical cancer, Prostate cancer, thyroid cancer.

According to 2012 statistics approximately 14.1 million cases are reported and 8.2 million deaths are reported. Lung, Liver, Stomach and bowel cancers cause the most common deaths among the worldwide that accounts nearly half of all the cancer deaths. About 70% increase in the cases are to be expected over the next 2 decades. In males 5 most common sites of cancer are diagnosed in 2012 were lung, prostate, colorectal and liver cancers. In females 5 most common sites diagnosed were breast, colorectal, cervix, lung and stomach cancer. Nearly 60% of the world’s total new cases occur in the Africa, Asia and Central and South America regions. All over the world Denmark ranks 1st in the cancer deaths USA is accompanied next to it.

ConferenceSeries Ltd  which is comprised of 3000+ Global Events with over 600+ Conferences, 1200+ Symposiums and 1200+Workshops on diverse Medical, Pharmaceutical, Clinical, Engineering, Science, Technology, Business and Management field is organizing conferences all over the globe. It hosts numerous Cancer Conferences, Cancer meeting, global cancer conference, European Oncology Conferences, Surgical oncology like skin cancer conference, breast cancer conference, liver cancer conference, lung cancer meetings, and Oncology Conferences where knowledge transfer takes place through debates, round table discussions, poster presentations, workshops, symposia and exhibitions and which helps get possibilities for treating the diseases with new era, technology and research.



Why Brussels???

Brussels, a region of Belgium comprising 19 municipalities, is a city of contrasts with enormous diversity, experiencing cool climates all throughout the year. Brussels is also becoming known as a mecca of style, art, and design having bilingualism of Modern French and Old Dutch.

Machine learning and deep learning technologies have seen a recent growth in trend towards their applications in personalised and predictive medicine. The ML models are designed with an aim to supervise the progression of cancer within a patient and aid in its treatment. Cancer is quite a diverse condition, which means that an early diagnosis and timely screening is instrumental for treatment. An array of popular ML techniques is used in Cancer Prognosis including and not limited to Artificial Neural Networks, Decision Trees, Support Vector Machines, Bayesian Networks and other Deep Learning approaches. Each of these methodologies contribute to the development of predictive models. Each model developed is expected to substantially improve the accuracy of susception and recurrence prediction. However, a number of published studies that appear to have build over these models lack validation and/or appropriate testing. In this review, we analyse and present a view on recent development of ML approaches that are applied in Cancer Prognosis and Prediction modelling.

Nasopharyngeal carcinomas (NPCs) are consistently associated with the Epstein–Barr virus (EBV). As Bcl-2 and Bcl-X are co-expressed in EBV-transformed B-lymphocytes, we attempted to determine their status in malignant NPC cells. A retrospective series of 100 NPC ...

Invitation
Conference Series LLC welcomes you to attend the 2nd Cancer Diagnostics Conference & Expo during May 08-10, 2017 Barcelona, Spain.
We cordially invite all the participants who are interested in sharing their knowledge and research in the arena of 2nd Cancer Diagnostics Conference & Expo.
Cancer Diagnostics 2017 anticipates more than 200 participants around the globe with thought provoking Keynote lectures, Oral and Poster presentations. The attending delegates include Editorial Board Members of related Conference Series LLC Journals.
This is an excellent opportunity for the delegates from Universities and Institutes to interact with the world class Scientists.
The intending participants can confirm their participation by registering for the conference along with your colleagues. Avail the delegate early bird offer.
The main theme of the conference is “An insight into Advancing New methods of Cancer Diagnostics”

Regards,


Cancer Diagnostics 2017
Operating Committee
Cancer
Diagnostics 2017

Loss of heterozygosity (LOH) in the 15q14-21 and 13q12-13 regions can contribute to the inactivation of RAD51 and BRCA2 genes implicated in the pathogenesis of breast cancer. We investigated allelic losses in microsatellites in the RAD51 and BRCA2 regions, and their association with clinicopathological parameters in breast cancer. The LOH analysis was performed by amplifying DNA by PCR, using D15S118, D15S214, D15S1006 polymorphic markers in the 15q14-21 region and D13S260, D13S290 polymorphic markers in the 13q12-13 region in 36 sporadic breast cancer cases. LOH in the RAD51 region ranged from 29% to 46% and in the BRCA2 region from 38% to 43% of informative cases. Eleven percent of the breast cancer cases displayed LOH for at least one studied marker in the RAD51 region exclusively. On the other hand, 44% of cases manifested statistically significant LOH for at least one microsatellite marker concomitantly in the RAD51 and BRCA2 regions. LOH in the RAD51 region similarly as in the BRCA2 region appeared to correlate with steroid receptors content and lymph node status. The obtained results indicate that alteration in RAD51 region may contribute to the disturbances of DNA repair involving RAD51 and/or BRCA2 penetration and thus enhance the risk of breast cancer development.

Optical spectroscopy methods have had considerable impact in the field of biomedical diagnostics, providing novel methods for the early or noninvasive diagnosis of various medical conditions. Among them, fluorescence spectroscopy has been the most widely explored mainly because fluorescence is highly sensitive to the biochemical makeup of tissues. It has been shown that tumors were easily detected on account of altered fluorescence properties with respect to fluorescence of ordinary tissue. Breast cancer is one of the most commonly diagnosed cancers among women in the world and also it is one of the leading causes of deaths from cancer for the female population. However, when detected in early stage, it is one of the most treatable forms of cancer. Therefore, fluorescence technologies could be highly beneficial in early detection and timely treatment of cancer. This chapter presents main results and conclusions that have been reported on the use of fluorescence spectroscopy for the investigation of breast cancer. It also gives an overview on the instruments and methodology of measurements, on the main endogenous fluorophores present in tissues, on the tissue fluorescence, and on the statistical methods that aid interpretations of fluorescence spectra. Finally, examples of using various fluorescence techniques, such as excitation, emission and synchronous spectroscopy, excitation-emission matrices, and lifetimes, for the breast cancer diagnosis are presented.

Background: Patient engagement in research agenda setting is increasingly being seen as a strategy to improve the responsiveness of healthcare to patient priorities. Implementation of low-dose computed tomography (LDCT) screening for lung cancer is suboptimal, suggesting that research is needed. Objectives: This study aimed to describe an approach by which a Veteran patient group worked with other stakeholders to develop a research agenda for LDCT screening and to describe the research questions that they prioritized.

Computer aided diagnosis (CAD) systems evaluate the conspicuous structure. Most of the existing diagnosis methods used mammogram mass characteristics but in the proposed technique microcalcification (MC) characteristics are used. In this project, cancer cells are diagnosis using the steps like mammogram image, pre-processing techniques, segmentation, classification, fuzzy logic and Receiver Operating Characteristics (ROC) curve analysis. Mammogram images are collected from the National Institute of Cancer. Pre-processing technique performed using normalization and median filtering. Based on the local threshold method, segmentation is done to identify the location of microcalcification present cells. Classification technique includes Perceptron algorithm and case based reasoning (CBR) method. Perceptron algorithm is used to classify the microcalcification present cells and microcalcification absent cells.CBR is used to classify the microcalcification present cells into following classes initial, very small, small, medium, high, very high. Fuzzy logic used for decision making purpose. And system performance analyzed using ROC curve analysis. This method provides better performance (95%) compare to the previous diagnosis techniques.

Vietnamese American men are over 10 times more likely to be diagnosed with liver cancer than their white counterparts. This health disparity is attributable to high rates of hepatitis B virus (HBV) infection. Our study objective was to examine factors associated with HBV testing among Vietnamese men. A population-based survey was conducted in Seattle. The questionnaire content was guided by an earlier qualitative study and the Health Behavior Framework. The survey was completed by 345 men (response rate: 80%). About one-third (34%) of the respondents reported they had not been tested for HBV. The following factors were associated (P<0.01) with previous testing in bivariate comparisons: having a regular source of care and regular provider; knowing that HBV can be spread during childbirth; believing HBV can cause liver cancer; and doctor(s) had recommended testing as well as had asked doctor(s) for testing. Three variables were independently associated with HBV testing in a logistic regression model: regular source of care (OR=4.5; 95% CI=2.6–7.9), physician recommendation (OR=2.3, 95% CI=1.3–4.0), and knowing HBV can be spread during childbirth (OR=2.1; 95% CI=1.2–3.9). Low levels of HBV testing remain a public health problem in some Vietnamese American sub-groups. Health education about HBV transmission may stimulate patients to seek testing. Intervention programs should specifically target Vietnamese men without a regular source of health care and physicians who serve Vietnamese communities.

Obesity has been associated with lower serum testosterone, theoretically resulting in decreased PSA production. Obesity has also been associated with prostatic enlargement, making the detection of existent cancer more difficult. Together these findings would result in an apparent protective effect of obesity on prostate cancer risk due to technical detection issues unrelated to cancer biology. We examined the association between BMI, and PSA and prostate weight in a cohort of men undergoing RP. We evaluated the association of BMI with prostate weight and PSA using linear regression, adjusting for patient age at RP, year of RP, race, and pathological stage and grade in 1,414 men treated with RP between 1988 and 2004 at the 5 equal access medical centers that comprise the Shared Equal Access Regional Cancer Hospital Database. On multivariate analysis increasing BMI was associated with increasing prostate weight but only in men younger than 63 years and not in men 63 years or older (p-trend &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;0.001 and 0.44, respectively). In men younger than 63 years mean multivariate adjusted prostate weight +/- SE in those with a BMI of less than 25 vs 30 to 34.9 kg/m was 33.8 +/- 1.4 vs 41.4 +/- 1.6 gm. There was no significant association between BMI and preoperative PSA (p-trend = 0.70). In a cohort of men undergoing RP obesity was associated with larger prostate size but only in younger men. There was no association between BMI and PSA. Assuming equal PSA, the degree of prostatic enlargement observed in younger obese men in this study would be expected to result in a modest decrease in the odds of detecting prostate cancer in a contemporary series of PSA screened men due to the decreased sensitivity of cancer detection related to larger prostate size. Obesity may appear protective for prostate cancer in younger men due to technical issues unrelated to cancer biology.

Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric propertie...

The efficiency of seed yield decreases in cancer in the field of healthcare. Therefore, it is automatically possible to recognize cancers in order to increase the yield in farming. The majority of the system, however, is affected by the inability to detect due to different cancer patterns. We introduce in this paper a computer vision model that helps create a system for acquiring images in real time, extracting features and classifying the images. The grader determines whether the cancer is diseased or not. For the classification of images in real time, we use Deep neural network (DNN). Cancer experimental findings demonstrate that the classification rate for the proposed method is higher than other existing methods.