A5019025712- Colorectal Cancer Screening and Detection
- Gastric Cancer Management and Outcomes
- Image Retrieval and Classification Techniques
- AI in cancer detection
- Global Cancer Incidence and Screening
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Gut microbiota and health
- Esophageal Cancer Research and Treatment
- Gastrointestinal Bleeding Diagnosis and Treatment
- Helicobacter pylori-related gastroenterology studies
- Inflammatory mediators and NSAID effects
- Explainable Artificial Intelligence (XAI)
- Diverticular Disease and Complications
- Colorectal Cancer Surgical Treatments
- Genetic factors in colorectal cancer
- Cancer, Lipids, and Metabolism
- Healthcare cost, quality, practices
- Multiple and Secondary Primary Cancers
- Esophageal and GI Pathology
- Enhanced Recovery After Surgery
- Cancer survivorship and care
- Pancreatic and Hepatic Oncology Research
- Chemical synthesis and alkaloids
- Gallbladder and Bile Duct Disorders
Cancer Registry of Norway
2017-2024
Telemark Hospital
2017-2024
University of Oslo
2017-2024
Norwegian Institute of Public Health
2024
Østfold Hospital Trust
2019
Automatic detection of diseases by use computers is an important, but still unexplored field research. Such innovations may improve medical practice and refine health care systems all over the world. However, datasets containing images are hardly available, making reproducibility comparison approaches almost impossible. In this paper, we present KVASIR, a dataset from inside gastrointestinal (GI) tract. The collection classified into three important anatomical landmarks clinically...
Abstract Artificial intelligence is currently a hot topic in medicine. However, medical data often sparse and hard to obtain due legal restrictions lack of personnel for the cumbersome tedious process manually label training data. These constraints make it difficult develop systems automatic analysis, like detecting disease or other lesions. In this respect, article presents HyperKvasir , largest image video dataset gastrointestinal tract available today. The collected during real gastro-...
The comparative effectiveness of sigmoidoscopy and fecal immunochemical testing (FIT) for colorectal cancer (CRC) screening is unknown.Individuals aged 50-74 years living in Southeast Norway were randomly invited between 2012 2019 to either once-only flexible or FIT every second year. Colonoscopy was recommended after if any polyp ≥10 mm, ≥3 adenomas, advanced CRC found or, subsequent to, >15 μg hemoglobin/g feces. Data this report obtained complete recruitment both groups included 2 full...
Bowel preparation (cleansing) is considered to be a key precondition for successful colonoscopy (endoscopic examination of the bowel). The degree bowel cleansing directly affects possibility detect diseases and may influence decisions on screening follow-up intervals. An accurate assessment quality therefore important. Despite use reliable validated scales, grading vary from one doctor another. objective automated would contribute reduce such inequalities optimize medical resources. This...
INTRODUCTION: To examine the association between low-dose aspirin use and risk of colorectal cancer (CRC). METHODS: In this nationwide cohort study, we identified individuals aged 50 years or older residing for 6 months more in Norway 2004–2018 obtained data from national registers on drug prescriptions, occurrence, sociodemographic factors. Multivariable Cox regression models were used to estimate CRC risk. addition, calculated number potentially averted by use. RESULTS: We included...
Artificial intelligence is currently a hot topic in medicine. The fact that medical data often sparse and hard to obtain due legal restrictions lack of personnel perform the cumbersome tedious labeling leads limitations for what would be possible achieve with automatic analysis. In this respect, article presents HyperKvasir which largest image video dataset gastrointestinal tract available today. collected during real gastro- colonoscopy examinations at Bærum Hospital Norway partly labeled...
Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary methods. To aid in the development of a non-invasive test with improved sensitivity specificity, we have initiated prospective biomarker study (CRCbiome), nested within large randomized trial Norway. We aim to develop microbiome-based classification algorithm identify advanced colorectal lesions...
Public health systems should guarantee universal access to care services, including cancer screening. We assessed whether certain population subgroups were underrepresented among participants in colorectal screening with sigmoidoscopy and faecal immunochemical testing (FIT). Between 2012 2019, about 140 000 individuals aged 50 74 years randomly invited once-only or first round of FIT Our study included 46 919 70 019 between 2017. used logistic regression models evaluate if demographic...
Neural networks, in the context of deep learning, show much promise becoming an important tool with purpose assisting medical doctors disease detection during patient examinations. However, current state learning is something a "black box", making it very difficult to understand what internal processes lead given result. This not only true for non-technical users but among experts as well. lack understanding has led hesitation implementation these methods mission-critical fields, many...
Objectives To assess detection rates for colorectal cancer (CRC) and advanced adenomas in asymptomatic CRC screening participants bowel symptoms association with adenoma. Design Cross-sectional study. Setting Two centres. Participants 42 554 men women, aged 50–74 years, participating a randomised trial. 36 059 underwent sigmoidoscopy (and follow-up colonoscopy if positive sigmoidoscopy) 6495 after faecal immunochemical test (FIT). Primary secondary outcome measures Proportion of diagnosed or...
The possible protective effect of aspirin on risk colorectal cancer (CRC) is still highly debated.We used data from Bowel Cancer Screening in Norway, a trial randomizing individuals general population, aged 50-74 years, to flexible sigmoidoscopy or faecal immunochemical test (FIT), study the association between use and detection CRC two precursors: adenomas advanced serrated lesions (ASL). Prescriptions low-dose were obtained Norwegian prescription database. Logistic regression was estimate...
Automatic detection of diseases is a growing field interest, and machine learning in form deep neural networks are frequently explored as potential tool for the medical video analysis. To both improve "black box"-understanding assist administrative duties writing an examination report, we release automated multimedia reporting software dissecting network to learn intermediate analysis steps, i.e., adding new level understanding explainability by looking into algorithms decision processes....
Analysis of medical videos for detection abnormalities and diseases requires both high precision recall, but also real-time processing live feedback scalability massive screening entire populations. Existing work on this field does not provide the necessary combination retrieval accuracy performance.; [email protected] paper, a multimedia system is presented where aim to tackle automatic analysis from human gastrointestinal (GI) tract. The includes whole pipeline data collection, analysis,...
Consistent participation in colorectal cancer (CRC) screening with repeated fecal immunochemical test (FIT) is important for the success of program. We investigated whether lifestyle risk factors CRC were related to inconsistent up four rounds FIT-screening.
The BioMedia 2019 ACM Multimedia Grand Challenge is the first in a series of competitions focusing on use multimedia for different medical use-cases. In this year's challenge, participants are asked to develop efficient algorithms which automatically detect variety findings commonly identified gastrointestinal (GI) tract (a part human digestive system). purpose task methods aid doctors performing routine endoscopy inspections GI tract. paper, we give detailed description four tasks present...
ABSTRACT Background The positivity thresholds of faecal immunochemical testing (FIT) in colorectal cancer (CRC) screening vary between countries. Aims To explore the trade‐off colonoscopies performed, adverse events and lesions detected at different FIT a Norwegian CRC trial. Methods We included first participation biennial for 47,265 individuals aged 50–74 years. Individuals with > 15 μg Hb/g faeces were referred colonoscopy. estimated number colonoscopies, events, screen‐detected CRCs,...
Repeated rounds of faecal immunochemical testing (FIT) for occult blood is a common method screening colorectal cancer (CRC). However, the time interval between FIT not thoroughly investigated. In CRC trial in South-Eastern Norway, individuals were invited biennial 2012 and 2019. The positivity threshold was >15 mcg haemoglobin/g faeces (mcg/g). Due to organizational challenges, randomly varied 1.5 3.5 years, forming natural experiment. We investigated detection rate advanced neoplasia (AN:...
Organized cancer screening programs should be equally accessible for all groups in society. We assessed differences participation colorectal (CRC) among different immigrant groups. Between 2012 and 2019, 140,000 individuals aged 50 to 74 years were randomly invited sigmoidoscopy or repeated faecal immunochemical test (FIT) a CRC trial. In this study, we included 46,919 70,018 the first round of FIT between 2017. examined difference non-immigrants immigrants, within by geographic area origin,...
In the future, medical doctors will to an increasing degree be assisted by deep learning neural networks for disease detection during examinations of patients. order make qualified decisions, black box must opened increase understanding reasoning behind decision machine system. Furthermore, preparing reports after is a significant part work-day, but if we already have system dissecting network understanding, same tool can used automatic report generation. this demo, describe that analyses...