Solving problems is smart, preventing them is wise: Lessons learned from the 2nd International <scp>DKFZ</scp> Conference on Cancer Prevention

Gillmann, Clarissa; Pajor, Gábor; Ramadori, Pierluigi; Albers, Peter; Mons, Ute; Steindorf, Karen; Kentner, Susan; Baumann, Michaël

doi:10.1002/ijc.33502

Cited by 2 publications

(3 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such issues were also discussed at the Second International DKFZ Conference on Cancer Prevention. 7 With this in mind, WCRF's new Cancer Prevention Awareness Week campaign (March 20-26, 2021) will seek to highlight to the UK public the latest guidance and messages on cancer prevention. It will ask people to sign a "Prevention Pledge" in support of WCRF's 10 key recommendations, pledging to make them part of their everyday lives.…”

Section: Why It's Crucial That a New Uk Cancer Control Awareness Camp...mentioning

confidence: 99%

“…Such issues were also discussed at the Second International DKFZ Conference on Cancer Prevention. 7 With this in mind, WCRF's new Cancer Prevention Awareness…”

mentioning

confidence: 99%

“…This is especially so against a backdrop of messaging that's not yet well known or accepted by the general population. Such issues were also discussed at the Second International DKFZ Conference on Cancer Prevention 7 …”

mentioning

confidence: 99%

See 2 more Smart Citations

Why it's crucial that a new UK cancer control awareness campaign is underpinned by robust research

Shattock

2021

Intl Journal of Cancer

View full text Add to dashboard Cite

show abstract

Section: Why It's Crucial That a New Uk Cancer Control Awareness Camp...mentioning

confidence: 99%

“…Such issues were also discussed at the Second International DKFZ Conference on Cancer Prevention. 7 With this in mind, WCRF's new Cancer Prevention Awareness…”

mentioning

confidence: 99%

See 1 more Smart Citation

Why it's crucial that a new UK cancer control awareness campaign is underpinned by robust research

Shattock

2021

Intl Journal of Cancer

View full text Add to dashboard Cite

show abstract

Machine Learning for Online Automatic Prediction of Common Disease Attributes Using Never-Ending Image Learner

et al. 2022

View full text Add to dashboard Cite

The rapid increase in Internet technology and machine-learning devices has opened up new avenues for online healthcare systems. Sometimes, getting medical assistance or healthcare advice online is easier to understand than getting it in person. For mild symptoms, people frequently feel reluctant to visit the hospital or a doctor; instead, they express their questions on numerous healthcare forums. However, predictions may not always be accurate, and there is no assurance that users will always receive a reply to their posts. In addition, some posts are made up, which can misdirect the patient. To address these issues, automatic online prediction (OAP) is proposed. OAP clarifies the idea of employing machine learning to predict the common attributes of disease using Never-Ending Image Learner with an intelligent analysis of disease factors. Never-Ending Image Learner predicts disease factors by selecting from finite data images with minimum structural risk and efficiently predicting efficient real-time images via machine-learning-enabled M-theory. The proposed multi-access edge computing platform works with the machine-learning-assisted automatic prediction from multiple images using multiple-instance learning. Using a Never-Ending Image Learner based on Machine Learning, common disease attributes may be predicted online automatically. This method has deeper storage of images, and their data are stored per the isotropic positioning. The proposed method was compared with existing approaches, such as Multiple-Instance Learning for automated image indexing and hyper-spectrum image classification. Regarding the machine learning of multiple images with the application of isotropic positioning, the operating efficiency is improved, and the results are predicted with better accuracy. In this paper, machine-learning performance metrics for online automatic prediction tools are compiled and compared, and through this survey, the proposed method is shown to achieve higher accuracy, proving its efficiency compared to the existing methods.

show abstract

Solving problems is smart, preventing them is wise: Lessons learned from the 2nd International DKFZ Conference on Cancer Prevention

Cited by 2 publications

References 69 publications

Why it's crucial that a new UK cancer control awareness campaign is underpinned by robust research

Why it's crucial that a new UK cancer control awareness campaign is underpinned by robust research

Machine Learning for Online Automatic Prediction of Common Disease Attributes Using Never-Ending Image Learner

Contact Info

Product

Resources

About