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Is the AI buzz too loud?
There is a plethora of application areas where AI-based systems can help healthcare, says one developer, but only if the technologies are leveraged with care and policymakers keep up with effective regulation.
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Study: sound regulation needed for AI-assisted clinical diagnosis
In theory, AI systems scan patient data and deliver faster, more accurate diagnoses than can be achieved currently, but stakeholders say new policy guidelines are needed to ensure patient safety.
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AI: bringing healthcare to the people?
With increasing frequency, “datathons” are expanding doctor-data scientist collaborations and expanding access to electronic medical records to improve patient care.
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First of a kind clinical use of AI/ML in Radiology shows promise and is being commercialized now
Around the world, the application of artificial intelligence (AI) and machine learning (ML) in medical imaging is a hot topic. While research work will undoubtedly continue and expand, there are also growing examples of AI and ML being used in real-world, clinical settings.
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AI is offering patients lower risks and richer insights
AI-based cardio evaluation has allowed doctors to change their recommended treatment plan for many patients, stakeholders say, meaning some patients who were due to receive stenting or a bypass were able to be treated with medication instead.
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How AI is improving patient care while lowering costs
The point of the in-roads being made in AI and robotics, experts noted at a recent tech summit, is to help provide “high-quality healthcare to everybody, at lower costs.”
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Study: AI plus EHRs yield better influenza forecasting
The study suggests the new method produces the most accurate estimates of influenza activity available to date, a week ahead of traditional healthcare-based reports.
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CEO: learning where to use AI is as important as learning how
The key to successful use of AI, says one leader, is corporate responsibility and education in how AI should be used, its capabilities and its limitations.
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GE taps Vanderbilt U as immunotherapy development partner
The two organizations intend to combine their data science, genomic, imaging and cellular analysis capabilities to help improve clinical decision-making.