scholarly journals Colorectal cancer screening methods

2016 ◽  
Vol 32 (3) ◽  
pp. 1453-1458
Author(s):  
Dusan Popovic ◽  
Tamara Alempijevic ◽  
Nada Kovacevic ◽  
Milan Spuran ◽  
Dragan Tomic ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Screening Methods

scholarly journals Scope of Artificial Intelligence in Screening and Diagnosis of Colorectal Cancer

2020 ◽  
Vol 9 (10) ◽  
pp. 3313 ◽  
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Aman Ali ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Narrow Band Imaging ◽  
Screening Methods ◽  
Polyp Detection ◽  
Mortality And Morbidity ◽  
Magnifying Chromoendoscopy

Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant mortality and morbidity, which can be reduced by early diagnosis with an effective screening test. Integrating artificial intelligence (AI) and computer-aided detection (CAD) with screening methods has shown promising colorectal cancer screening results. AI could provide a “second look” for endoscopists to decrease the rate of missed polyps during a colonoscopy. It can also improve detection and characterization of polyps by integration with colonoscopy and various advanced endoscopic modalities such as magnifying narrow-band imaging, endocytoscopy, confocal endomicroscopy, laser-induced fluorescence spectroscopy, and magnifying chromoendoscopy. This descriptive review discusses various AI and CAD applications in colorectal cancer screening, polyp detection, and characterization.

574 RECENT TRENDS IN COLORECTAL CANCER SCREENING METHODS BASED ON MEDICARE CLAIMS DATA

2020 ◽  
Vol 158 (6) ◽  
pp. S-121
Author(s):  
Ahmet B. Ozbay ◽  
Lila J. Finney Rutten ◽  
John B. Kisiel ◽  
Paul Limburg ◽  
Marcus Parton
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Claims Data ◽  
Screening Methods ◽  
Medicare Claims ◽  
Recent Trends ◽  
Medicare Claims Data

scholarly journals Modeling Individual Patient Preferences for Colorectal Cancer Screening Based on Their Tolerance for Complications Risk

2016 ◽  
Vol 37 (3) ◽  
pp. 204-215 ◽  
Author(s):  
Glen B. Taksler ◽  
Adam T. Perzynski ◽  
Michael W. Kattan
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Life Expectancy ◽  
Colorectal Cancer Screening ◽  
Flexible Sigmoidoscopy ◽  
Screening Method ◽  
Screening Strategy ◽  
Screening Methods ◽  
Average Risk ◽  
National Guidelines

Introduction. Recommendations for colorectal cancer screening encourage patients to choose among various screening methods based on individual preferences for benefits, risks, screening frequency, and discomfort. We devised a model to illustrate how individuals with varying tolerance for screening complications risk might decide on their preferred screening strategy. Methods. We developed a discrete-time Markov mathematical model that allowed hypothetical individuals to maximize expected lifetime utility by selecting screening method, start age, stop age, and frequency. Individuals could choose from stool-based testing every 1 to 3 years, flexible sigmoidoscopy every 1 to 20 years with annual stool-based testing, colonoscopy every 1 to 20 years, or no screening. We compared the life expectancy gained from the chosen strategy with the life expectancy available from a benchmark strategy of decennial colonoscopy. Results. For an individual at average risk of colorectal cancer who was risk neutral with respect to screening complications (and therefore was willing to undergo screening if it would actuarially increase life expectancy), the model predicted that he or she would choose colonoscopy every 10 years, from age 53 to 73 years, consistent with national guidelines. For a similar individual who was moderately averse to screening complications risk (and therefore required a greater increase in life expectancy to accept potential risks of colonoscopy), the model predicted that he or she would prefer flexible sigmoidoscopy every 12 years with annual stool-based testing, with 93% of the life expectancy benefit of decennial colonoscopy. For an individual with higher risk aversion, the model predicted that he or she would prefer 2 lifetime flexible sigmoidoscopies, 20 years apart, with 70% of the life expectancy benefit of decennial colonoscopy. Conclusion. Mathematical models may formalize how individuals with different risk attitudes choose between various guideline-recommended colorectal cancer screening strategies.

scholarly journals Intelligent recognition of colorectal cancer combining application of computer-assisted diagnosis with deep learning approaches

2022 ◽  
Vol 12 (1) ◽  
pp. 738
Author(s):  
Akella S. Narasimha Raju ◽  
Kayalvizhi Jayavel ◽  
Tulasi Rajalakshmi
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Premalignant Lesions ◽  
Computer Assisted ◽  
Screening Methods ◽  
Learning Approaches ◽  
Computer Assisted Diagnosis ◽  
Assisted Diagnosis

<span>The malignancy of the colorectal testing methods has been exposed triumph to decrease the occurrence and death rate; this cancer is the relatively sluggish rising and has an extremely peculiar to develop the premalignant lesions. Now, many patients are not going to colorectal cancer screening, and people who do, are able to diagnose existing tests and screening methods. The most important concept of this motivation for this research idea is to evaluate the recognized data from the immediately available colorectal cancer screening methods. The data provided to laboratory technologists is important in the formulation of appropriate recommendations that will reduce colorectal cancer. With all standard colon cancer tests can be recognized agitatedly, the treatment of colorectal cancer is more efficient. The intelligent computer assisted diagnosis (CAD) is the most powerful technique for recognition of colorectal cancer in recent advances. It is a lot to reduce the level of interference nature has contributed considerably to the advancement of the quality of cancer treatment. To enhance diagnostic accuracy intelligent CAD has a research always active, ongoing with the deep learning and machine learning approaches with the associated convolutional neural network (CNN) scheme.</span>

scholarly journals An Overview of Colorectal Cancer Screening

2008 ◽  
Vol 53 (4) ◽  
pp. 31-37 ◽  
Author(s):  
SA Goodbrand ◽  
RJC Steele
Keyword(s):  
Colorectal Cancer ◽  
United Kingdom ◽  
Cancer Screening ◽  
High Risk ◽  
Colorectal Cancer Screening ◽  
Current Practice ◽  
Screening Methods ◽  
Average Risk ◽  
The United Kingdom

Colorectal cancer ranks highly amongst all cancer sites in incidence and contributes to a substantial number of cancer related deaths in the United Kingdom. However, screening of average risk individuals has been shown to reduce both disease associated mortality and incidence. This paper provides an overview of both current and future screening methods for colorectal cancer, as well as current practice for screening in both average and high risk individuals.

Trends in screening for prostate cancer

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 1542-1542
Author(s):  
F. Eisinger ◽  
J. Morere ◽  
X. Pivot ◽  
J. Blay ◽  
Y. Coscas ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Representative Sample ◽  
Prostate Cancer Screening ◽  
Specific Antigen ◽  
Screening Methods ◽  
The Future ◽  
Systematic Recommendation

1542 Background: Screening for prostate cancer is still in debate. In France, there is no financial barrier for individuals to be screened with the prostate-specific antigen (PSA) test, and there is no recommendation for mass screening. Methods: Two nationwide observational studies were carried out in France. The first one, EDIFICE 1, was conducted in 2005 among a representative sample of 1504 subjects aged between 40 and 75 years and a representative sample of 600 general practitioners (GPs). The second one, EDIFICE 2, was conducted in 2008 with the same methodology. Results: General population: In 2005, 36% of the interviewed male population aged between 50 and 75 years declared having undergone a screening test, compared to 49% in 2008 (OR = 1.63 CI95% 1.25; 2.12). Prostate cancer screening increased in all age groups, however, the most significant increase can be observed in the population aged between 50 and 54 years: 18% in 2005 versus 35% in 2008 (OR = 2.43 CI95% 1.31; 4.52). This trend for increasing testing will probably be confirmed in the future since 57% of males never screened plan to undergo a test, and only 16% of those who did screening plan to stop. The expected participation in the future will be close to 70%. Physicians: In 2005, 58% of GPs systematically recommended prostate cancer screening for their male consultants ages 50 to 74, in 2008 the figure is 65% (OR = 1.32 CI95%1.04; 1.66). For prostate cancer screening, a GP's gender has no significant impact. Systematic recommendation for both breast and colorectal cancer screening has an impact on recommending prostate cancer screening as well; OR = 2.9 (CI95% 2.0–4.4) and OR = 2.0 (CI95% 1.3–3.2) respectively. The GP's age is not associated with a higher rate of systematic recommendation. Conclusions: We have observed in France a significant growth in prostate cancer screening: more persons screened, more often, at a younger age. Despite the lack of consistent evidence, persons and GPs exposed to mass communication and campaign for breast and colorectal cancer screening might infer that screening is valuable for other conditions. No significant financial relationships to disclose.

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