The Stanford University research team led by Andrew Ng found that machine learning models better recognize arrhythmias from electrocardiograms (ECGs) than experts. Applying this model not only enhances the reliability of arrhythmia diagnosis, but also enables high-quality medical services in areas where medical resources are scarce. At the same time, it also marks that machine learning may revolutionize medicine. In recent years, researchers have found that machine learning technology can identify a variety of diseases from medical images, including breast cancer, skin cancer, and eye diseases.
An in-depth learning algorithm trained by the Stanford University research team to identify different types of arrhythmias. Some arrhythmias can cause serious consequences, even sudden death, but it is very difficult to identify these arrhythmias. Patients are often required to wear ECG sensors for several weeks, but even then, it is difficult for doctors to distinguish between benign arrhythmias and disorders requiring immediate treatment. The research team works with iRhythm, a company that manufactures portable ECG equipment. They collected 300,000 30-second clips from different arrhythmia patients. During the deep learning process, the team entered these clips into a large simulated neural network and fine-tuned the parameters until the algorithm could accurately identify the problematic ECG signal. However, deep learning is a particularly opaque form of machine learning that is difficult to convince doctors and patients to apply algorithms. However, there is no doubt that a revolution is about to come.
Shirt custom company uses machine vision system to tailor the customer
The startup, Original Stitch, uses artificial intelligence to customize shirts for customers. Original Stitch is committed to providing men with a one-of-a-kind shirt that is implemented through the company's Bodygram vision system. If you want to customize the shirt, the user can take out a shirt that he likes at home, put a piece of paper on the shirt, and then take a picture with the phone, the system can generate measurement results.
The Bodygram model also broadens the future of Original Stitch, such as shoes and womenswear. At present, Bodygram's measurement is not so accurate. If the first measurement is wrong, Original Stitch will re-create the shirt for the customer, but the customer needs to wait for a while. The company's goal is to make it easier for people to customize their shirts, especially for those who like to shop online or are unwilling to try on a hanger shirt at the mall to buy a shirt.
Github released a new feature "code owner" that will automatically receive notifications when the code changes.
Github introduces a new feature "code owner" that makes it easier to identify the code owner when the code is modified, and the code owner to review the changes. The code owner can determine the team or individual to which a piece of code belongs, and users receive automatic notifications when they change the code. To start the code owner in Github, the user must create a new file called CODEOWNERS in the root directory. Github admits that this is inspired by Google Chrome's "owners files" feature.
In addition, Github has added a "protected branches" feature to ensure that project collaborators are unable to make permanent changes. It is a more rigorous review process. Once this feature is enabled, the project collaborator must go through the review of the code owner to modify the directory or file. These features are very useful for Github, a platform with 20 million users and 57 million repositories. The company also recently released the "Open Source Friday" feature, which, as the name suggests, encourages individuals and organizations to take some time each Friday to contribute to open source projects.
Soft Sanitary Napkin,Sanitary Napkin Price,Low Cost Sanitary Napkins,Daily Dry Sanitary Napkin
Shandong Tianzige International Trade Co., Ltd , https://www.sdbabydiapers.com