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

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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.


AI-Powered Metabolic Health Program from January.ai Accurately Predicts Individualized Glycemic Response in People with Type 2 Diabetes

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WIRE)--New data presented today at the 80th American Diabetes Association Scientific Sessions – A Virtual Experience unveiled a new AI algorithm from January.ai. In an in-house study of 1,022 participants, the algorithm effectively predicted individualized glycemic response to specific meals in people with type 2 diabetes and pre-diabetes. This algorithm is critical to the company's goal of developing and offering a program that provides people with highly personalized food and activity recommendations that drive positive behavior change and improved health. In the Sugar Challenge study, January.ai After a few days of data-gathering to develop an individualized model, the algorithm accurately predicted glucose response to future meals in the absence of any further CGM data, a finding that supports further exploration of the impact of AI models with intermittent CGM use.


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.


Artificial Intelligence in Cardiology: Present and Future

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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.

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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

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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.


FitByte Uses Sensors on Eyeglasses To Automatically Monitor Diet

CMU School of Computer Science

Food plays a big role in our health, and for that reason many people trying to improve their diet often track what they eat. A new wearable from researchers in Carnegie Mellon University's School of Computer Science helps wearers track their food habits with high fidelity. FitByte, a noninvasive, wearable sensing system, combines the detection of sound, vibration and movement to increase accuracy and decrease false positives. It could help users reach their health goals by tracking behavioral patterns, and gives practitioners a tool to understand the relationship between diet and disease and to monitor the efficacy of treatment. The device tracks all stages of food intake.