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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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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

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Pattern Recognition in Machine Learning [Basics & Examples]

Knowledge Hut

This can be done by finding regularities in the data, such as correlations or trends, or by identifying specific features in the data. Pattern recognition is used in a wide variety of applications, including Image processing, Speech recognition, Biometrics, Medical diagnosis, and Fraud detection.

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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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Data Science in Pharmaceutical Industry [Use Cases + Examples]

Knowledge Hut

Data science in pharmaceutical industry is extensively used to improve its operations through applications such as predictive modeling, segmentation analysis, machine learning algorithms, visualization tools, etc., In this article, we have explained about data science in pharma, their use cases, o pportunities, and more.

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Living on the Edge: How to Accelerate Your Business with Real-time Analytics

Cloudera

Consider the potentially catastrophic outcome of two autonomous vehicles on a collision course or taking a beat too long to act on an alert from an implanted medical device. . And that comes down to being able to act on data at the precise time it requires action. Real-time Demands.

Medical 118
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Driving Innovation and Efficiency with Gen AI in Life Sciences

Snowflake

Today, generative AI-powered tools and algorithms are being used for diagnostics, predicting disease outbreaks and targeted treatment plans — and the industry is just getting started. Medical imaging: Embedding models in AI can identify disease markers in images, helping with early diagnosis and treatment.