Remove Deep Learning Remove Medical Remove Unstructured Data
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Natural Language Processing in Healthcare: Using Text Analysis for Medical Documentation and Decision-Making

AltexSoft

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data.

Medical 52
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Deep Learning vs Machine Learning: What’s The Difference?

Knowledge Hut

On that note, let's understand the difference between Machine Learning and Deep Learning. Below is a thorough article on Machine Learning vs Deep Learning. We will see how the two technologies differ or overlap and will answer the question - What is the difference between machine learning and deep learning?

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Length of Stay in Hospital: How to Predict the Duration of Inpatient Treatment

AltexSoft

This article describes how data and machine learning help control the length of stay — for the benefit of patients and medical organizations. The length of stay (LOS) in a hospital , or the number of days from a patient’s admission to release, serves as a strong indicator of both medical and financial efficiency.

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How to get datasets for Machine Learning?

Knowledge Hut

can help users to get started with Machine Learning. Open Dataset Finders To solve any problem in data science, be it in the field of Machine Learning, Deep Learning, or Artificial Intelligence , one needs a dataset that can be input into the model to derive insights. A technology has no significance without data.

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Medical Datasets for Machine Learning: Aims, Types and Common Use Cases

AltexSoft

Everyday the global healthcare system generates tons of medical data that — at least, theoretically — could be used for machine learning purposes. Regardless of industry, data is considered a valuable resource that helps companies outperform their rivals, and healthcare is not an exception. Medical data labeling.

Medical 52
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Generative AI vs. Predictive AI: Understanding the Differences

Edureka

paintings, songs, code) Historical data relevant to the prediction task (e.g., Unlike traditional AI systems that operate on pre-existing data, generative AI models learn the underlying patterns and relationships within their training data and use that knowledge to create novel outputs that did not previously exist.

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Processing medical images at scale on the cloud

Tweag

Machine Learning (ML). Deep Learning. To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. Artificial Intelligence (AI). Neural Networks (NNs). Most training pipelines and systems are designed to handle fairly small, sub-megapixel images.

Medical 60