AI News, Guest Blog
KWF is investing 2.7 million euros in five different studies at Radboudumc.
The awards are part of the new round of funding by DCS, in which over 34 million euros will be granted to Dutch cancer research.
Breast cancer prediction: How Artificial Intelligence can save lives?
Even though artificial intelligence-powered programs and tools are helping businesses automate tasks, improve efficiencies, reduce costs and most importantly reduce the burden of an employee’s shoulders, there are people who fear it might take away jobs and reduce the aspect of human touch from a product or service.
Constance Lehman, MD, Ph.D., chief of the breast imaging division at Massachusetts General Hospital (MGH) and a professor of radiology at Harvard Medical School highlights the fact that our current tools to predict the future risks are simply not accurate in healthcare.
However, connecting human intelligence to the power of clinical expertise and unparalleled data processing capabilities of machine learning like deep learning and advanced neural networks is presenting an altogether new frontier for precise and personalized medicine, diagnostics along with treatment.
Moreover, using artificial intelligence and its subsidiaries to expand the healthcare industry’s capabilities for more effective screenings, reduced pain points in the care process, along with augmented clinical decision making in healthcare can help the industry save millions of dollars every year and enhance the impact of the patient’s voice in their treatment. Talking about breast cancer, the point is that human interpretation of images is highly subjective.
According to recent research by the MIT Technology Review and GE Healthcare, it was discovered that some radiologists designate less than 10 percent of breast tissue as dense, while other radiologists will label more than 80 percent of the mammograms in the same manner.
The research further indicates that an algorithm trained on more than 70,000 images consistently outperformed the commonly used risk model in the industry, in spite of the fact that there was no additional patient data provided to it.
The best part of the model was that it was able to more effectively screen for breast cancer using less information than human doctors, relying solely on X-ray images, while medical experts had access to patient’s histories and mamograms.
- On 19. juni 2021
Local researchers use artificial intelligence to predict cancer treatment outcomes
Local researchers use artificial intelligence to predict cancer treatment outcomes.
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