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With its improved productivity and accuracy and more personalized experience, AI is revolutionizing medical imaging. According to Signify Research, the world market for AI in medical imaging — comprising software for automated detection, quantification, decision support, and diagnosis — will reach US$2 billion by 2023.
Revenue Forecast for Global Medical Image Analysis Software (Signify Research)
AI technologies utilized in medical imaging processing include deep learning, machine learning, data mining, etc. These are capable of achieving a range of goals in disease screening, disease diagnosis and medical surgery.
AI Energizes Medical Image Processing: Medical image processing is essentially the application of computer vision technology. AI technologies such as machine learning and deep learning are used in the intelligent analysis of imaging data processed by computer vision technologies such as imaging registration and fusion; and can assist doctors in medical image labeling, disease diagnosis, and surgery.
Medical imaging data is combined with physical signs of patients, medical history, genetic information, identity information and other non-image data in the training of AI algorithms, this can help the machine analyze the data in higher dimensions and extract the most essential characteristics. Exploring implied correlations behind the disease can assist doctors in diagnosing disease more accurately.
Watson Studio provide a choice of tools for the full AI lifecycle including best of-breed open source and tools. The user can choose between code or no-code tools to build and train your own ML/DL models, or easily retrain and customize pre-trained Watson APIs. Use the rich capabilities and controls to fine tune your models and automate the feedback loop of your models so they become smarter over time and continually adapt to changing conditions.
The first step of the workflow starts with connecting and accessing data. Data scientists spend up to 80% of their time finding and preparing data, and 57% of data scientists said that cleaning and organizing data is the least enjoyable part of their job. The problem isn’t just limited to data scientists. Business analysts face similar struggles obtaining the data they need to build reports — often having to wait weeks for their IT team to extract data from the source systems.
To address the issue, we provide integrated capability to refine and wrangle data with Data Refinery, a tool that makes fast, self-service data preparation a reality. Watson Studio comes with more than 35 data connectors to the most popular data sources, whether they are in the IBM Cloud, 3rd party Clouds or application, or on-premises.
Watson tools and pre-trained models
Once you are connected to data, the next step is to build and train models. Application developers can get started with best-in-class pre-trained Watson APIs , which are the most accurate in the industry. These models will understand sentiment, classify topics in text, identify personality insights or recognize objects in a photo. We provide access to well documented APIs with samples and code snippets in the most popular programming languages.
By continuously training your models against the latest data, users can ensure that they continue to reflect today’s business realities, giving the organization the insight it needs to make smarter decisions and seize competitive advantage.
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Author :Ethan Ze/ DOTS • LINES- Digital Medical News Hunter
We focused on Technology, AI, Data Science, Medical solution. And will be provide complete artificial intelligence medical applications and industry knowledge as much as possible.
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