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Identifying tumor cells at the single-cell level using machine learning - Genome Biology

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Cancer is a disease that stems from the disruption of cellular state. Through genetic perturbations, tumor cells attain cellular states that give them proliferative advantage over the surrounding normal tissue [1]. The inherent variability of this process has hampered efforts to find highly effective common therapies, thereby ushering the need for precision medicine [2]. The scale of single-cell experiments is poised to revolutionize personalized medicine by effective characterization of the complete heterogeneity within a tumor for each individual patient [3, 4]. Recent expansion of single-cell sequencing technologies has exponentially increased the scale of knowledge attainable through a single biological experiment [5].


Wi-Fi sensing has the potential to be disruptive – TechTarget

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With help from AI and machine learning, Wi-Fi sensing detects movement in the Wi-Fi environment. While it sounds promising, the technology still has a …





Improving CrowdStrike Falcon Detection Content with the Gap Analysis Team

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A Deep Dive into Custom Spark Transformers for Machine Learning Pipelines … How CrowdStrike Achieves Lightning-Fast Machine Learning Model …




About Us – ICML

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The International Conference on Machine Learning (ICML) is the premier … of the branch of artificial intelligence known as machine learning.


Artificial Intelligence and Machine Learning in Trading: How are they changing the world of Trading?

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Machine Learning is a subject of Artificial Intelligence that enables software solutions to make decisions based on accurate and calculated …