Conclusion (~1,700 words).
All backed up by over 200 references (~6,500 words).
We must stop crediting the wrong people for inventions made by others.
Instead let s heed the recent call in the journal
Nature: Let 2020 be the year in which we value those who ensure that
science is self-correcting [SV20].
Like those who know me can testify, finding and citing original sources of scientific and technological innovations is important to me, whether they are mine or other people s [DL1][DL2][HIN][NASC1-9]. The present page is offered as a resource for computer scientists who share this inclination.
By grounding research in its true intellectual foundations and crediting the original inventors,
RSNA: Lung Cancer Screening Predicts Risk of Death from Heart Disease
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A deep learning algorithm accurately predicts the risk of death from cardiovascular disease using information from low-dose CT exams performed for lung cancer screening, according to a study published in Radiology: Cardiothoracic Imaging.
Lung screening studies show that heavy smokers die from cardiovascular disease as much as from lung cancer. The work offers a direction for future research to precisely pinpoint which calcifications are dangerous. OAK BROOK, Ill. (PRWEB) April 15, 2021 A deep learning algorithm accurately predicts the risk of death from cardiovascular disease using information from low-dose CT exams performed for lung cancer screening, according to a study published in Radiology: Cardiothoracic Imaging.
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IMAGE: Projections of all aligned chest CT scans show feasibility of slab-based quantification of calcium, resulting in an average image. For alignment, only translation, rotation, and scaling were allowed, resulting in. view more
Credit: Radiological Society of North America
OAK BROOK, Ill. - A deep learning algorithm accurately predicts the risk of death from cardiovascular disease using information from low-dose CT exams performed for lung cancer screening, according to a study published in
Radiology: Cardiothoracic Imaging.
Cardiovascular disease is the leading cause of mortality worldwide. It even outpaces lung cancer as the leading cause of death in heavy smokers.
Waist size may better predict AFib risk in men
Sarah Amandolare, American Heart Association News
April 15, 2021
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Body mass index may be more helpful in predicting the risk of a common type of irregular heartbeat in women, while waist size may better predict that risk in men, new research suggests.
The link between obesity and atrial fibrillation, or AFib – when the heart beats irregularly and often too fast – is well established. But researchers wanted to understand the extent to which body fat distribution might predict AFib risk among men and women.
The researchers analyzed BMI, waist circumference and electrocardiogram data gathered between 2008 and 2013 from more than 2 million older adults in the U.S. and United Kingdom who didn t have cardiovascular conditions, including heart failure and stroke. The study s lead author, Dr. Michiel Poorthuis of University Medical Center Utrecht in the Netherlands, described it as probably the largest study of its
Scientific American
Researchers are searching for possible links between unusual clotting and the Oxford-AstraZeneca coronavirus vaccine
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The very rare occurrence of a mysterious blood-clotting disorder among some recipients of the Oxford–AstraZeneca COVID-19 vaccine has researchers scrambling to uncover whether and how the inoculation could trigger such an unusual reaction.
After weeks of investigation, the European Medicines Agency (EMA) announced on 7 April that there is a possible link between the clots and the vaccine. Even so, the clotting disorder described today in two reports in
The New England Journal of Medicine is so uncommon that the benefits of the vaccine still outweigh its risks, EMA executive director Emer Cooke told reporters. “These are very rare side effects,” she said. “The risk of mortality from COVID is much greater than the risk of mortality from these side effects.”