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Handling Missing Data For Advanced Machine Learning

#artificialintelligence

Throughout this article, you will become good at spotting, understanding, and imputing missing data. We demonstrate various imputation techniques on a real-world logistic regression task using Python. Properly handling missing data has an improving effect on inferences and predictions. This is not to be ignored. The first part of this article presents the framework for understanding missing data.


New algorithm uses artificial intelligence to help manage type 1 diabetes – IAM Network

#artificialintelligence

Researchers and physicians at Oregon Health & Science University, using artificial intelligence and automated monitoring, have designed a method to help people with type 1 diabetes better manage their glucose levels. The research was published in the journal Nature Metabolism. "Our system design is unique," said lead author Nichole Tyler, an M.D.-Ph.D. student in the OHSU School of Medicine. "We designed the AI algorithm entirely using a mathematical simulator, and yet when the algorithm was validated on real-world data from people with type 1 diabetes at OHSU, it generated recommendations that were highly similar to recommendations from endocrinologists." That's significant because the people with diabetes typically go three to six months between appointments with their endocrinologist.


New algorithm uses artificial intelligence to help manage type 1 diabetes

#artificialintelligence

Researchers and physicians at Oregon Health & Science University, using artificial intelligence and automated monitoring, have designed a method to help people with type 1 diabetes better manage their glucose levels. The research was published in the journal Nature Metabolism. "Our system design is unique," said lead author Nichole Tyler, an M.D.-Ph.D. student in the OHSU School of Medicine. "We designed the AI algorithm entirely using a mathematical simulator, and yet when the algorithm was validated on real-world data from people with type 1 diabetes at OHSU, it generated recommendations that were highly similar to recommendations from endocrinologists." That's significant because the people with diabetes typically go three to six months between appointments with their endocrinologist.


New algorithm uses artificial intelligence to help manage type 1 diabetes

#artificialintelligence

Researchers and physicians at Oregon Health & Science University, using artificial intelligence and automated monitoring, have designed a method to help people with type 1 diabetes better manage their glucose levels. The research was published in the journal Nature Metabolism. "Our system design is unique," said lead author Nichole Tyler, an M.D.-Ph.D. student in the OHSU School of Medicine. "We designed the AI algorithm entirely using a mathematical simulator, and yet when the algorithm was validated on real-world data from people with type 1 diabetes at OHSU, it generated recommendations that were highly similar to recommendations from endocrinologists." That's significant because the people with diabetes typically go three to six months between appointments with their endocrinologist.


Emerging Applications for Intelligent Diabetes Management

AI Magazine

Diabetes management is a difficult task for patients, who must monitor and control their blood glucose levels in order to avoid serious diabetic complications. It is a difficult task for physicians, who must manually interpret large volumes of blood glucose data to tailor therapy to the needs of each patient. This paper describes three emerging applications that employ AI to ease this task: (1) case-based decision support for diabetes management; (2) machine learning classification of blood glucose plots; and (3) support vector regression for blood glucose prediction. The first application provides decision support by detecting blood glucose control problems and recommending therapeutic adjustments to correct them. The second provides an automated screen for excessive glycemic variability.


Covid-19 Is History's Biggest Translation Challenge

WIRED

You, a person who's currently on the English-speaking internet in The Year of The Pandemic, have definitely seen public service information about Covid-19. You've probably been unable to escape seeing quite a lot of it, both online and offline, from handwashing posters to social distancing tape to instructional videos for face covering. But if we want to avoid a pandemic spreading to all the humans in the world, this information also has to reach all the humans of the world--and that means translating Covid PSAs into as many languages as possible, in ways that are accurate and culturally appropriate. It's easy to overlook how important language is for health if you're on the English-speaking internet, where "is this headache actually something to worry about?" is only a quick Wikipedia article or WebMD search away. For over half of the world's population, people can't expect to Google their symptoms, nor even necessarily get a pamphlet from their doctor explaining their diagnosis, because it's not available in a language they can understand.


Artificial Intelligence in Cardiology: Present and Future

#artificialintelligence

For the purpose of this narrative review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and medicine and cardiology subspecialties. Articles were reviewed and selected for inclusion on the basis of relevance. This article highlights that the role of ML in cardiovascular medicine is rapidly emerging, and mounting evidence indicates it will power the new tools that drive the field. Among other uses, AI has been deployed to interpret echocardiograms, to automatically identify heart rhythms from an ECG, to uniquely identify an individual using the ECG as a biometric signal, and to detect the presence of heart disease such as left ventricular dysfunction from the surface ECG.6x6Attia, Z.I., Kapa, S., Lopez-Jimenez, F. et al.


IoT is drastically changing the world for the better.

#artificialintelligence

IoT is drastically changing the world for the better. There was a time when internet connectivity was available only on phones and computers. In the past decade, this focus has shifted to all technologies. Gradually, we are seeing the development of devices that connect to the internet. All these devices collect and share data to make our lives easier. You must know what IoT is by now, but for general understanding IoT is a broad umbrella.


AI's Communication Upsides

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Artificial intelligence has a bad rap. Facial recognition algorithms -- like those used by law enforcement agencies around the country -- encourage racism. Digital assistants, such as Siri and Alexa, make children ruder. Predictive algorithms, like those employed by Facebook, narrow our perspectives. Meanwhile, language translators, including Google Translate, are said to hinder meaningful emotional connection.


Predicting Diabetes Using a Machine learning Approach

#artificialintelligence

Using the ML approach, we can now assess diabetes in the patient. Learn more about how the algorithms used are dramatically changing health care. Diabetes is one of the deadliest diseases in the world. It is not only a disease, but also a creator of a variety of diseases such as heart attacks, blindness, and kidney diseases. The usual detection process is that patients visit the diagnostic center, consult their physician, and sit tight for a day or more to get their reports.