State of Colorectal Cancer Awareness Report
To uncover attitudes and the biggest challenges facing colorectal cancer awareness and screening, BGI Genomics today released its , marking the first-ever global survey report on the world’s third most common cancer. This report is released on World Health Day, April 07, 2023, in line with achieving Health For All, and seeks to motivate action to tackle the health challenges of today and tomorrow.
Despite 51.5% reporting that there is insufficient information about CRC and 34.5% citing costs holding them back from CRC screening, the report reveals several optimistic findings. For example, 88.8% are more willing to go for screening upon learning about the 5-year survival rate of 90% for early CRC detection."Early CRC detection offers the best outcome for individuals and healthcare policy.
Doctors are the biggest factor for respondents to go for screening in the absence of symptoms. 62.5% will heed their doctor’s advice to undergo CRC screening. Therefore, it is vital that doctors are made more aware of CRC symptoms, ask the right questions to identify potential hereditary genetic risk and offer patients a range of screening options, to fit different lifestyles and budgets. In our opinion, the best colorectal cancer screening test is the one a patient will do.
To read and view country or region-level comparisons, please see link to access the full BGI Genomics 2023.
Österreich Neuesten Nachrichten, Österreich Schlagzeilen
Similar News:Sie können auch ähnliche Nachrichten wie diese lesen, die wir aus anderen Nachrichtenquellen gesammelt haben.
Bruce Willis's family praised by Angela Rippon for raising dementia awareness after diagnosisThe Die Hard and Pulp Fiction star was diagnosed with frontotemporal dementia (FTD) in March last year. Since then Alzheimers.org.uk has seen a surge in visitors.
Weiterlesen »
Shrewsbury grandmother to run first London Marathon at 70Jan Dodds is raising money to fight the eye condition macular degeneration, which she’s had for a decade. Read her story:
Weiterlesen »
What the world’s hottest MBA courses reveal about 21st-century businessThere may be no better lens through which to examine the future of management than the most oversubscribed courses on Stanford University’s MBA programme
Weiterlesen »
Five red flag stomach ache symptoms you should see your GP aboutTwo experts share some of the signs to look out for ahead of Bowel Cancer Awareness Month
Weiterlesen »
Automatic disease prediction from human gut metagenomic data using boosting GraphSAGE - BMC BioinformaticsBackground The human microbiome plays a critical role in maintaining human health. Due to the recent advances in high-throughput sequencing technologies, the microbiome profiles present in the human body have become publicly available. Hence, many works have been done to analyze human microbiome profiles. These works have identified that different microbiome profiles are present in healthy and sick individuals for different diseases. Recently, several computational methods have utilized the microbiome profiles to automatically diagnose and classify the host phenotype. Results In this work, a novel deep learning framework based on boosting GraphSAGE is proposed for automatic prediction of diseases from metagenomic data. The proposed framework has two main components, (a). Metagenomic Disease graph (MD-graph) construction module, (b). Disease prediction Network (DP-Net) module. The graph construction module constructs a graph by considering each metagenomic sample as a node in the graph. The graph captures the relationship between the samples using a proximity measure. The DP-Net consists of a boosting GraphSAGE model which predicts the status of a sample as sick or healthy. The effectiveness of the proposed method is verified using real and synthetic datasets corresponding to diseases like inflammatory bowel disease and colorectal cancer. The proposed model achieved a highest AUC of 93%, Accuracy of 95%, F1-score of 95%, AUPRC of 95% for the real inflammatory bowel disease dataset and a best AUC of 90%, Accuracy of 91%, F1-score of 87% and AUPRC of 93% for the real colorectal cancer dataset. Conclusion The proposed framework outperforms other machine learning and deep learning models in terms of classification accuracy, AUC, F1-score and AUPRC for both synthetic and real metagenomic data.
Weiterlesen »
Johnson & Johnson agrees to pay $8.9bn to settle claims that talc caused cancerJohnson & Johnson faces about 40,000 lawsuits from people claiming its talc products caused cancer. While it denies the allegations, it has agreed to pay almost $9bn to claimants.
Weiterlesen »