| 1. |
- Spjuth, Ola, 1977-, et al.
(författare)
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E-Science technologies in a workflow for personalized medicine using cancer screening as a case study
- 2017
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Ingår i: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 24:5, s. 950-957
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Tidskriftsartikel (refereegranskat)abstract
- Objective: We provide an e-Science perspective on the workflow from risk factor discovery and classification of disease to evaluation of personalized intervention programs. As case studies, we use personalized prostate and breast cancer screenings.Materials and Methods: We describe an e-Science initiative in Sweden, e-Science for Cancer Prevention and Control (eCPC), which supports biomarker discovery and offers decision support for personalized intervention strategies. The generic eCPC contribution is a workflow with 4 nodes applied iteratively, and the concept of e-Science signifies systematic use of tools from the mathematical, statistical, data, and computer sciences.Results: The eCPC workflow is illustrated through 2 case studies. For prostate cancer, an in-house personalized screening tool, the Stockholm-3 model (S3M), is presented as an alternative to prostate-specific antigen testing alone. S3M is evaluated in a trial setting and plans for rollout in the population are discussed. For breast cancer, new biomarkers based on breast density and molecular profiles are developed and the US multicenter Women Informed to Screen Depending on Measures (WISDOM) trial is referred to for evaluation. While current eCPC data management uses a traditional data warehouse model, we discuss eCPC-developed features of a coherent data integration platform.Discussion and Conclusion: E-Science tools are a key part of an evidence-based process for personalized medicine. This paper provides a structured workflow from data and models to evaluation of new personalized intervention strategies. The importance of multidisciplinary collaboration is emphasized. Importantly, the generic concepts of the suggested eCPC workflow are transferrable to other disease domains, although each disease will require tailored solutions.
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| 2. |
- Beiranvand, Samira, et al.
(författare)
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Ten years incidence of cancer in Iran : a systematic review and meta-analysis
- 2018
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Ingår i: Clinical Epidemiology and Global Health. - : Elsevier. - 2452-0918 .- 2213-3984. ; 6:2, s. 94-102
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundDesigning and implementation of screening programs depend on greatly epidemiologic basic data in every country. Also Variation in the incidence of various cancers in our country has been a favorite topic.ObjectivesThis systematic review was conducted to provide an overall perspective about incidence, geographical and age distribution of cancers in Iran.MethodsA comprehensive search were done according to MOOSE guideline criteria in national and international databases for selecting eligible articles from 2005 to 2015. After screening titles and abstracts, duplicated and irrelevant studies were excluded. Selected papers are written in Persian or English. The standard error of the cancer incidence was calculated based on the binomial distribution. Because of the significant heterogeneity observed among the results, we used a random-effects model combine the results of the primary studies. Moreover, a sensitivity analysis was undertaken to explore the effects of the risk of bias and other sources of heterogeneity.ResultsOverall 16 articles met eligibility criteria for inclusion. The total incidence of cancer was 19.4 and 17.2 per hundred thousand of people in males and females respectively. The five most common cancers in male were: Lymphoma, leukemia, esophagus, stomach, colorectal and in the female are: breast, colorectal, stomach, thyroid and esophagus. The highest incidence rate was seen in Golestan Province and in the age group over 65 years.ConclusionAccording to increasing incidence rate of cancers in Iran, Development, holding and accomplish of universal public cancer control program should be the first precedence for health policy.
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| 3. |
- Carlsson, Marianne, et al.
(författare)
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Evaluation of quality of life/life satisfaction in women with breast cancer in complementary and conventional care
- 2004
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Ingår i: Acta Oncologica. - OSLO : TAYLOR & FRANCIS AS. - 0284-186X .- 1651-226X. ; 43:1, s. 27-34
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Tidskriftsartikel (refereegranskat)abstract
- The aim was to study the perceived quality of life/life satisfaction in a sample of women with breast cancer who were treated in a hospital with alternative/complementary care and the same variables in individually matched patients who received only conventional medical treatment. A non-randomized controlled trial design with repeated measurements was used. Sixty women with breast cancer treated with anthroposophic medicine (ABCW) and 60 with conventional medicine (CBCW) were included and 36 matched pairs took part on all occasions. The quality of life was measured by the EORTC QLQ-C30 and the Life Satisfaction Questionnaire (LSQ). The comparisons were calculated as effect sizes (ES). The women in the ABCW group reported small or moderate effects, expressed as ES, on their quality of life/life satisfaction compared to their matched "twins'' in the CBCW group at the 1-year follow-up in 15 out of 21 scales/factors. It was concluded that the women who had chosen anthroposophic care increased their perceived quality of life/life satisfaction according to the methodology of the study.
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| 4. |
- Çayır, Sercan, et al.
(författare)
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Patch-based approaches to whole slide histologic grading of breast cancer using convolutional neural networks
- 2023
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Ingår i: Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods. - : Elsevier. - 9780323961295 - 9780323996815 ; , s. 103-118
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Bokkapitel (refereegranskat)abstract
- In early-stage breast cancer, the Nottingham Histologic Grading (NHG) is a strong prognostic factor. It is made up of nuclear pleomorphism, tubular formation, and mitotic count evaluation. Major grade disagreement is low (1.5%), but inter-observer agreement in grading among pathologists is moderate. Grading errors or inconsistencies caused by a variety of factors may jeopardize patient care and overall survival. It has been demonstrated that the assessment of the NHG is comparable to light microscopy and Whole Slide Images (WSI), which are digitized images of histopathologic slides. Because AI-based breast cancer grading is a new area of pathology, there are inherent difficulties in training AI models. We mitigate the high computational cost associated with the dimensions of WSIs by using a patch-based approach, and we mitigate the problems associated with the availability of training data by carefully annotating and labeling these patches. This chapter describes a fully automated computer-aided patch-based system that employs deep learning (DL) methods. Nuclear pleomorphism, tubular formation, and mitotic count are all graded using the proposed method. In addition, to train and test the DL methods in the proposed approach, we created an in-house individual dataset for pleomorphism, tubule detection, nuclei, and mitosis detection, which consists of 23.283, 10.117, 2.993, and 9.816 annotated patches extracted from WSIs of breast tissue with varying hematoxylin and eosin stains, respectively. These WSIs were obtained from a variety of patients who had been diagnosed with invasive ductal carcinoma. Four different difficult tasks are solved using the proposed computer-aided DL patch-based system. Semantic segmentation is used for tubular formation, object detection is used for nuclei detection, and image classification is used for mitotic count and nuclear pleomorphism. To obtain the results, we fine-tuned pre-trained (on ImageNet) DL architectures such as EfficientNet backbone U-Net, Scaled-Yolov4, DenseNet-161, and VGG-11 with our dataset for tubule segmentation, nuclei detection, and mitosis and nuclear pleomorphism classification tasks. We demonstrate that data augmentation is critical for improving the accuracy of patch-based DL models, which serve as the foundation of our WSI grading system. The proposed method resulted in reproducible histologic scores with F1- values of 94%, 94.1%, and 50.7% for nuclear pleomorphism classification, tubule formation segmentation, and mitotic classification, respectively. The results of the experiments presented in this chapter show promise for clinical translation of the DL algorithms described. Using the proposed approach to perform histological grading of WSIs will reduce the subjectivity associated with pathologist-assigned grades. © 2023 Elsevier Inc. All rights reserved.
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| 5. |
- Forssell, Henrik, et al.
(författare)
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A proposed model for prediction of survival based on a follow-up study in unresectable pancreatic cancer
- 2013
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Ingår i: BMJ Open. - : BMJ Publishing Group. - 2044-6055. ; 3:12, s. 1-6
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: To define an easy-to-use model for prediction of survival time in patients with unresectable pancreatic cancer in order to optimise patient' care. DESIGN: An observational retrospective study on patients with unresectable pancreatic cancer. The initial radiographs at presentation of symptoms were reviewed and the maximum diameter of the primary tumour was determined. The occurrence of liver metastases and performance status that determines initiation of chemotherapy was also used in the regression analysis to identify prognostic subgroups. SETTING: County hospital in south-east of Sweden. POPULATION: Consecutive patients with unresectable pancreatic cancer who were diagnosed between January 2003 and May 2010 (n=132). MAIN OUTCOME MEASURES: Statistical analyses were performed using Stata V.13. Survival time was assessed with Kaplan-Meier analysis, log-rank test for equality of survivor functions and Cox regression for calculation of individual hazard based on tumour diameter, presence of liver metastases and initiation of chemotherapy treatment according to patient performance status. RESULTS: The individual hazard was log h=0.357 tumour size+1.181 liver metastases-0.989 performance status/chemotherapy. Three prognostic groups could be defined: a low-risk group with a median survival time of 6.7 (IQR 9.7) months, a medium-risk group with a median survival time of 4.5 (IQR 4.5) months and a high-risk group with a median survival time of 1.2 (IQR 1.7) months. CONCLUSIONS: The maximum diameter of the primary tumour and the presence of liver metastases found at the X-ray examination of patients with pancreatic cancer, in conjunction with whether or not chemotherapy is initiated according to performance status, predict the survival time for patients who do not undergo surgical resection. The findings result in an easy-to-use model for predicting the survival time.
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| 6. |
- Lekamlage, Charitha Dissanayake, et al.
(författare)
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Mini-DDSM : Mammography-based Automatic Age Estimation
- 2020
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Ingår i: ACM International Conference Proceeding Series. - New York, NY, USA : Association for Computing Machinery. - 9781450389044 ; , s. 1-6
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Konferensbidrag (refereegranskat)abstract
- Age estimation has attracted attention for its various medical applications. There are many studies on human age estimation from biomedical images. However, there is no research done on mammograms for age estimation, as far as we know. The purpose of this study is to devise an AI-based model for estimating age from mammogram images. Due to lack of public mammography data sets that have the age attribute, we resort to using a web crawler to download thumbnail mammographic images and their age fields from the public data set; the Digital Database for Screening Mammography. The original images in this data set unfortunately can only be retrieved by a software which is broken. Subsequently, we extracted deep learning features from the collected data set, by which we built a model using Random Forests regressor to estimate the age automatically. The performance assessment was measured using the mean absolute error values. The average error value out of 10 tests on random selection of samples was around 8 years. In this paper, we show the merits of this approach to fill up missing age values. We ran logistic and linear regression models on another independent data set to further validate the advantage of our proposed work. This paper also introduces the free-access Mini-DDSM data set. © 2020 ACM.
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| 7. |
- Tärnhuvud, Marie, et al.
(författare)
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Nursing interventions to improve the health of men with prostata cancer undergoing radiotherapy : A review
- 2007
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Ingår i: European Journal of Oncology Nursing. - : ELSEVIER. - 1462-3889. ; :11, s. 328-339
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to investigate what nurses do to improve the health of men who are receiving radiotherapy treatment due to prostata cancer. The method was a literature review using a systematic approach. The Cochrane Library, Medline and CINAHL databaseswere used in a search that covered the period from January 1994 to April 2006. The screening of 200 abstracts resulted in 14 articles corresponding to the research question,which were assessed according to scientific quality. Two independent reviewers performed the screening and quality assessment process using specific protocols. Two themes emerged: nurse-led care related to radiotherapy treatment and patients´experiences of radiotherapy treatment. The result show that there is strong scientific support for nurse-led follow-up care aimed at assisting patients by means of providing information on how to manage side effects (evidence grade A). In addition, there is moderate scientific support for the need to ensure that this information is structured, objective and concrete and that it can be provided by means of audiotapes or over the phone (evidence grade B) as well as weak scientific support for reporting patients´experiences of radiotherapy treatment (evidence grade C).
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