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ML helps researchers decipher immune system for cancer patients
Among other outcomes, the new algorithm predicted which patients had better responses to specific therapies and had better overall survival rates.
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Experts: Risk of AI bias should be “top of mind” for developers and execs
Recent research suggests AI and predictive algorithms can be less accurate for vulnerable populations and could exacerbate existing health disparities.
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Scientists tap AI to develop cancer-killing nanoparticles
Using the new platform, the team was able to simulate both simple tumors and more complex tumors with cancer stem cells, which are sometimes difficult to treat and lead to relapse of some cancer patients.
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The growing role of AI in cybersecurity
Since AI works 24/7, the report notes, the constant monitoring means that it can process large quantities of data and detect threats quickly.
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Work in progress: how the FDA intends to regulate AI
The FDA has several initiatives in the pipeline to address an array AI regulatory challenges, but officials say they still need private sector help to ensure steady progress.
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Governance group releases recommendations for AI testing guidelines
Following the DOME recommendations, say the stakeholders, healthcare providers and researchers will find emerging AI solutions increasingly relevant and useful.
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New AI improves accuracy of detecting colon cancer risk
Adenoma detection rates and, conversely, adenoma miss rates vary greatly across physicians performing colonoscopies, with miss rates ranging from six percent to 41 percent.
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Cybersecurity: the key to AI longterm success in healthcare
AI and machine learning models are expensive and time intensive to create but easy to replicate, so preventing access to systems is critical to protecting them from adversaries.
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Researchers use “federated learning” to help predict patient oxygen needs
Predicting oxygen needs for COVID patients will enable hospitals to care for patients while also ensuring adequate oxygen supplies throughout their organizations.