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Machine Learning Engineer - The Machine Learning Conference

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Overjet is an early-stage VC-backed startup building the future of data-driven dentistry. We are using AI to transform the $130B dental care market and improve patient outcomes. We are seeking an entrepreneurially-minded a highly skilled developer who is comfortable with backend software development including deploying machine learning models, loves challenges and is passionate about impacting lives. Please email your resume to careers@overjet.ai. Develop machine learning pipelines Deploy machine learning models for inference Implement and maintain metrics for tracking ML models performance Design and develop microservices and APIs related to data ingestion, machine learning and product quality Ensuring responsiveness of applications.


Deep learning - Deep Learning for Precision Health

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Magnetoencephalography (MEG) is a functional neuroimaging modality that records the magnetic fields induced by neuronal activity. It provides better temporal resolution than fMRI and is less affected by noise from intervening tissues than EEG. We propose a data driven, fully automated approach that extracts statistically independent MEG components and a convolutional neural network to discriminate the artifactual components from neuronal ones, without tedious manual labeling. Our custom, 10-layer Convolutional Neural Network (CNN) directly labels eye-blink artifacts. The spatial features the CNN learns are visualized using attention mapping, to reveal what it has learned and bolster confidence in the method's ability to generalize to unseen data.


AI and Machine Learning: Disrupting Healthcare

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The promise of artificial intelligence (AI) and machine learning to improve care and outcomes, lower the cost of care, and increase patient and provider satisfaction is fast-tracking these disruptive technologies for significant growth in healthcare in the immediate future. In a recent Healthcare IT News/HIMSS Analytics survey, about 35% of healthcare organizations plan to leverage artificial intelligence within two years – and more than 50% intend to do so within five years.* These technologies can categorize and analyze huge amounts of both structured and unstructured data to glean clinical insights to improve individual and population health through better diagnoses, disease pattern identification and treatment methods. They can improve infrastructure, workflows and data management, and other tasks and processes – increasing productivity, consistency and quality, and reducing costs and errors. They can improve the provider-patient experience, allowing physicians to spend more time with patients by automating time-intensive tasks like medical image analyzation, data entry, and procedure and condition monitoring.


Unintended Consequences of Machine Learning in Medicine

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Over the past decade, machine learning techniques have made substantial advances in many domains. In health care, global interest in the potential of machine learning has increased; for example, a deep learning algorithm has shown high accuracy in detecting diabetic retinopathy.1 There have been suggestions that machine learning will drive changes in health care within a few years, specifically in medical disciplines that require more accurate prognostic models (eg, oncology) and those based on pattern recognition (eg, radiology and pathology).


buquati.com

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While you're asking yourself how to leverage your business on machine/deep learning, many questions come up from data collection, preparation, labeling, modeling, training, testing, continuous development, continuous integration... BuQuaTi's Machine Learning Platform (BQT-MLP) is the unique platform in the market which can serve all three Google TensorFlow models; TensorFlow, TensorFlow Mobile, TensorFlow Lite. Our professional services acompanied by our Machine Learning Platform (BQT-MLP) enable your smart digital journey end to end; simplification, preparation, modeling, development, deployment, operations, analytics. More than 60% of the efforts in a data project like Machine Learning, go into data preparation; cleansing, transforming, and labeling. We manage all aspects, and propose efficient, a-class solutions.