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Deep Learning Approaches in Medical Image Segmentation

KDnuggets

Medical imaging has been revolutionized by the adoption of deep learning techniques. The use of this branch of machine learning has ushered in a new era of precision and efficiency in medical image segmentation, a central analytical process in modern healthcare diagnostics and treatment planning.

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Best Deep Learning Tools to Master in 2023

Knowledge Hut

We all have witnessed how Deep learning has emerged as one of the most promising domains of artificial intelligence, enabling machines to process, analyze and draw insights from vast amounts of data. And hence, it has become significant to master some of the major deep learning tools to work with this concept better.

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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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Top Deep Learning Projects Ideas in 2023 (For Beginners & Advanced) 

Knowledge Hut

In recent years, the field of deep learning has gained immense popularity and has become a crucial subset of artificial intelligence. Data Science aspirants should learn Deep Learning after taking a Data Science certificate online , which would enhance their skillset and create more opportunities for them.

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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. Medical Data: What to Consider When Working with Healthcare Information. In the medical sphere, sensitive details are called protected health information or PHI. Let’s sum up.

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Computer Vision in Healthcare: Creating an AI Diagnostic Tool for Medical Image Analysis

AltexSoft

Particularly, we’ll present our findings on what it takes to prepare a medical image dataset, which models show best results in medical image recognition , and how to enhance the accuracy of predictions. Medical image databases: abundant but hard to access. labeling data by medical experts to create a ground-truth dataset.

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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. It can be manually transformed into structured data by hospital staff, but it’s never a priority in the medical setting. Medical transcription.

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