CERVICAL CANCER CONFERENCE


Cervical Cancer Conference is one of the leading research topics in the international research conference domain. Cervical Cancer is a conference track under the Healthcare Conference which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Healthcare.

internationalconference.net provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of (Healthcare).

Cervical Cancer is not just a call for academic papers on the topic; it can also include a conference, event, symposium, scientific meeting, academic, or workshop.

You are welcome to SUBMIT your research paper or manuscript to Cervical Cancer Conference Track will be held at “Healthcare Conference in Paris, France in June 2019” - “Healthcare Conference in London, United Kingdom in August 2019” - “Healthcare Conference in New York, United States in October 2019” - “Healthcare Conference in Rome, Italy in December 2019” - “Healthcare Conference in London, United Kingdom in February 2020” - “Healthcare Conference in Barcelona, Spain in April 2020” .

Cervical Cancer is also a leading research topic on Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, Elsevier, Scopus, Web of Science.

INTERNATIONAL HEALTHCARE CONFERENCE

JUNE 26 - 27, 2019
PARIS, FRANCE

INTERNATIONAL HEALTHCARE CONFERENCE

AUGUST 21 - 22, 2019
LONDON, UNITED KINGDOM

  • Abstracts/Full-Text Paper Submission Deadline April 30, 2019
  • Notification of Acceptance/Rejection Deadline May 15, 2019
  • Final Paper and Early Bird Registration Deadline July 22, 2019
  • CONFERENCE CODE: 19HC08GB
  • One Time Submission Deadline Reminder

INTERNATIONAL HEALTHCARE CONFERENCE

OCTOBER 09 - 10, 2019
NEW YORK, UNITED STATES

  • Abstracts/Full-Text Paper Submission Deadline April 30, 2019
  • Notification of Acceptance/Rejection Deadline May 15, 2019
  • Final Paper and Early Bird Registration Deadline September 09, 2019
  • CONFERENCE CODE: 19HC10US
  • One Time Submission Deadline Reminder

INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 11 - 12, 2019
ROME, ITALY

  • Abstracts/Full-Text Paper Submission Deadline April 30, 2019
  • Notification of Acceptance/Rejection Deadline May 15, 2019
  • Final Paper and Early Bird Registration Deadline November 12, 2019
  • CONFERENCE CODE: 19HC12IT
  • One Time Submission Deadline Reminder

INTERNATIONAL HEALTHCARE CONFERENCE

FEBRUARY 18 - 19, 2020
LONDON, UNITED KINGDOM

  • Abstracts/Full-Text Paper Submission Deadline April 30, 2019
  • Notification of Acceptance/Rejection Deadline May 15, 2019
  • Final Paper and Early Bird Registration Deadline January 16, 2020
  • CONFERENCE CODE: 20HC02GB
  • One Time Submission Deadline Reminder

INTERNATIONAL HEALTHCARE CONFERENCE

APRIL 15 - 16, 2020
BARCELONA, SPAIN

  • Abstracts/Full-Text Paper Submission Deadline April 30, 2019
  • Notification of Acceptance/Rejection Deadline May 15, 2019
  • Final Paper and Early Bird Registration Deadline March 16, 2020
  • CONFERENCE CODE: 20HC04ES
  • One Time Submission Deadline Reminder
FINISHED

INTERNATIONAL HEALTHCARE CONFERENCE

MARCH 19 - 20, 2019
ISTANBUL, TURKEY

Healthcare Conference Call For Papers are listed below:

Previously Published Papers on "Cervical Cancer Conference"

  • Non-Melanoma Skin Cancer in Ha’il Region in the Kingdom of Saudi Arabia: A Clinicopathological Study
    Authors: Laila Seada, Nouf Al Gharbi, Shaimaa Dawa, Keywords: Non melanoma skin cancer, Hail Region, histopathology, BCC. DOI:10.5281/zenodo.2571910 Abstract: Although skin cancers are prevalent worldwide, it is uncommon in Ha’il region in the Kingdom of Saudi Arabia, mostly non-melanoma sub-type. During a 4-year period from 2014 to 2017, out of a total of 120 cases of skin lesions, 29 non-melanoma cancers were retrieved from histopathology files obtained from King Khalid Hospital. As part of the study, all cases of skin cancer diagnosed during 2014 -2017 have been revised and the clinicopathological data recorded. The results show that Basal cell carcinoma (BCC) was the most common neoplasm (36%), followed by cutaneous lymphomas (mostly mycosis fungoides 25%), squamous cell carcinoma (SCC) (21%) and dermatofibrosarcoma protuberans (DFSP) (11%). Only one case of metastatic carcinoma was recorded. BCC nodular type was the most prevalent, with a mean age 57.6 years and mean size 2.73 cm. SCC was mostly grade 2, with mean size 1.9 cm and an older mean age of 72.3 cm. Increased size of lesion positively correlated with older age (p = 0.001). Non-melanoma skin cancer in Ha’il region is not frequently encountered. BCC is the most frequent followed by cutaneous T-cell lymphomas and SCC. The findings in this study were in accordance with other parts of, but much lower than other parts of the world.
  • MITOS-RCNN: Mitotic Figure Detection in Breast Cancer Histopathology Images Using Region Based Convolutional Neural Networks
    Authors: Siddhant Rao, Keywords: Object detection, histopathology, breast cancer, mitotic count, deep learning, computer vision. DOI:10.5281/zenodo.1475004 Abstract: Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.
  • Grade and Maximum Tumor Dimension as Determinants of Lymphadenectomy in Patients with Endometrioid Endometrial Cancer (EEC)
    Authors: Ali A. Bazzi, Ameer Hamza, Riley O’Hara, Kimberly Kado, Karen H. Hagglund, Lamia Fathallah, Robert T. Morris, Keywords: Endometrial cancer, FIGO grade, lymphadenectomy, tumor size. DOI:10.5281/zenodo.1474801 Abstract: Introduction: Endometrial Cancer is a common gynecologic malignancy primarily treated with complete surgical staging, which may include complete pelvic and para-aortic lymphadenectomy. The role of lymphadenectomy is controversial, especially the intraoperative indications for the procedure. Three factors are important in decision to proceed with lymphadenectomy: Myometrial invasion, maximum tumor dimension, and histology. Many institutions incorporate these criteria in varying degrees in the decision to proceed with lymphadenectomy. This investigation assesses the use of intraoperatively measured MTD with and without pre-operative histologic grade. Methods: This study compared retrospectively EEC patients with intraoperatively measured MTD ≤2 cm to those with MTD >2 cm from January 1, 2002 to August 31, 2017. This assessment compared those with MTD ≤ 2cm with endometrial biopsy (EB) grade 1-2 to patients with MTD > 2cm with EB grade 3. Lymph node metastasis (LNM), recurrence, and survival were compared in these groups. Results: This study reviewed 222 patient cases. In tumors > 2 cm, LNM occurred in 20% cases while in tumors ≤ 2 cm, LNM was found in 6% cases (p=0.04). Recurrence and mean survival based on last follow up visit in these two groups were not statistically different (p=0.78 and 0.36 respectively). Data demonstrated a trend that when combined with preoperative EB International Federation of Gynecology and Obstetrics (FIGO) grade, a higher proportion of patients with EB FIGO Grade 3 and MTD > 2 cm had LNM compared to those with EB FIGO Grade 1-2 and MTD ≤ 2 cm (43% vs, 11%, p=0.06). LNM was found in 15% of cases in which lymphadenectomy was performed based on current practices, whereas if the criteria of EB FIGO 3 and MTD > 2 cm were used the incidence of LNM would have been 44% cases. However, using this criterion, two patients would not have had their nodal metastases detected. Compared to the current practice, the sensitivity and specificity of the proposed criteria would be 60% and 81%, respectively. The PPV and NPV would be 43% and 90%, respectively. Conclusion: The results indicate that MTD combined with EB FIGO grade can detect LNM in a higher proportion of cases when compared to current practice. MTD combined with EB FIGO grade may eliminate the need of frozen section sampling in a substantial number of cases.
  • Absorbed Dose Estimation of 177Lu-DOTATOC in Adenocarcinoma Breast Cancer Bearing Mice
    Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, Keywords: Breast cancer, compartmental modeling, 177Lu, dosimetry. DOI:10.5281/zenodo.1474561 Abstract: In this study, the absorbed dose of human organs after injection of 177Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, 177Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.
  • An Alternative and Complementary Medicine Method in Vulnerable Pediatric Cancer Patients: Yoga
    Authors: Ç. Erdoğan, T. Turan, Keywords: Cancer treatment, children, nursing, yoga. DOI:10.5281/zenodo.1340595 Abstract: Pediatric cancer patients experience multiple distressing, challenges, physical symptom such as fatigue, pain, sleep disturbance, and balance impairment that continue years after treatment completion. In recent years, yoga is often used in children with cancer to cope with these symptoms. Yoga practice is defined as a unique physical activity that combines physical practice, breath work and mindfulness/meditation. Yoga is an increasingly popular mind-body practice also characterized as a mindfulness mode of exercise. This study aimed to evaluate the impact of yoga intervention of children with cancer. This article planned searching the literature in this field. It has been determined that individualized yoga is feasible and provides benefits for inpatient children, improves health-related quality of life, physical activity levels, physical fitness. After yoga program, children anxiety score decreases significantly. Additionally, individualized yoga is feasible for inpatient children receiving intensive chemotherapy. As a result, yoga is an alternative and complementary medicine that can be safely used in children with cancer.
  • Hypothesis of a Holistic Treatment of Cancer: Crab Method
    Authors: Devasis Ghosh, Keywords: ATF3 dampening, auxin modulation, cancer, platelet activation, serotonin, stress, valproic acid. DOI:10.5281/zenodo.1317336 Abstract: The main hindrance to total cure of cancer is a) the failure to control continued production of cancer cells, b) its sustenance and c) its metastasis. This review study has tried to address this issue of total cancer cure in a more innovative way. A 10-pronged “CRAB METHOD”, a novel holistic scientific approach of Cancer treatment has been hypothesized in this paper. Apart from available Chemotherapy, Radiotherapy and Oncosurgery, (which shall not be discussed here), seven other points of interference and treatment has been suggested, i.e. 1. Efficient stress management. 2. Dampening of ATF3 expression. 3. Selective inhibition of Platelet Activity. 4. Modulation of serotonin production, metabolism and 5HT receptor antagonism. 5. Auxin, its anti-proliferative potential and its modulation. 6. Melatonin supplementation because of its oncostatic properties. 7. HDAC Inhibitors especially valproic acid use due to its apoptotic role in many cancers. If all the above stated seven steps are thoroughly taken care of at the time of initial diagnosis of cancer along with the available treatment modalities of Chemotherapy, Radiotherapy and Oncosurgery, then perhaps, the morbidity and mortality rate of cancer may be greatly reduced.
  • Thermalytix: An Advanced Artificial Intelligence Based Solution for Non-Contact Breast Screening
    Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu, Keywords: Breast Cancer Screening, Radiology, Thermalytix, Artificial Intelligence, Thermography. DOI:10.5281/zenodo.1316566 Abstract: Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups.  This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.
  • Identification of Disease Causing DNA Motifs in Human DNA Using Clustering Approach
    Authors: G. Tamilpavai, C. Vishnuppriya, Keywords: Bioinformatics, cancer motif, DNA, k-mers, Levenshtein distance, SOM. DOI:10.5281/zenodo.1316412 Abstract: Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.
  • Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach
    Authors: Rajvir Kaur, Jeewani Anupama Ginige, Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine. DOI:10.5281/zenodo.1316355 Abstract: With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.
  • miR-200c as a Biomarker for 5-FU Chemosensitivity in Colorectal Cancer
    Authors: Rezvan Najafi, Korosh Heydari, Massoud Saidijam, Keywords: Colorectal cancer, miR-200c, 5-FU resistance, E-cadherin, PTEN. DOI:10.5281/zenodo.1316345 Abstract: 5-FU is a chemotherapeutic agent that has been used in colorectal cancer (CRC) treatment. However, it is usually associated with the acquired resistance, which decreases the therapeutic effects of 5-FU. miR-200c is involved in chemotherapeutic drug resistance, but its mechanism is not fully understood. In this study, the effect of inhibition of miR-200c in sensitivity of HCT-116 CRC cells to 5-FU was evaluated. HCT-116 cells were transfected with LNA-anti- miR-200c for 48 h. mRNA expression of miR-200c was evaluated using quantitative real- time PCR. The protein expression of phosphatase and tensin homolog (PTEN) and E-cadherin were analyzed by western blotting. Annexin V and propidium iodide staining assay were applied for apoptosis detection. The caspase-3 activation was evaluated by an enzymatic assay. The results showed LNA-anti-miR-200c inhibited the expression of PTEN and E-cadherin protein, apoptosis and activation of caspase 3 compared with control cells. In conclusion, these results suggest that miR-200c as a prognostic marker can overcome to 5-FU chemoresistance in CRC.