High-quality image data is essential for training deep learning (DL) classifiers, yet data sharing is often limited by privacy concerns. We hypothesized that generative adversarial networks (GANs) could synthesize bone marrow smear (BMS) images…
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Repeated failings in the way scans are read are leading to delays in cancer diagnosis, unnecessary operations and avoidable deaths, England’s health ombudsman has warned.
Since the publication of a report in July 2021, which…
Alarming Gaps in Healthcare AI Detection
New research published in Nature Communications Medicine has exposed critical flaws in machine learning mortality prediction models currently used in healthcare settings. These AI systems failed to recognize approximately…
How Machine Learning Addresses Ancestral Bias
The risk of bias in artificial intelligence has been extensively documented, but a groundbreaking new tool is poised to transform genetic research by addressing critical ancestral bias in datasets….
What You Should Know:
– John Snow Labs, the AI for healthcare company launches Medical LLM Reasoner, the first commercially available healthcare-specific reasoning large language model (LLM).
– The LLM model represents a significant leap forward…
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In part 2 of our series on the basics of digital technology, we explore the deep learning tools that can improve medical image analysis and much more.
By John Halamka, M.D., President, Mayo Clinic Platform…
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Brain.space, the maker of an EEG helmet, announced an $11 million Series A Funding round led by Toyota Ventures, with participation by Mangrove Capital Partners and The Group Ventures. The company also received a $3.5…
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Advances in artificial intelligence are moving from machine learning models that analyze data to algorithms that can act on it with minimal human involvement across clinical, administrative and patient-facing workflows.Agentic AI, or autonomous agents,…
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Yonatan (Yoni) Savir, Assoc. Prof. Faculty of Medicine at Technion
While it’s only relatively recently that AI became a household term, the technology is already having a major impact on society. But perhaps AI’s greatest…
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Attention-deficit/hyperactivity disorder (ADHD), characterized by diagnostic complexity and symptom heterogeneity, is a prevalent neurodevelopmental disorder. Here, we explored the machine learning (ML) analysis of retinal fundus photographs as a noninvasive biomarker for ADHD screening…
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