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Headquarters of the Council of Higher Scientific Research (CSIC).

a bone scan Every two years for all women aged 50-69. Since 1990, that is The biggest testing challenge for the national health systemAnd it aims to prevent one of the most common cancers in Spain, that is Mother, The method is X-rays that detect potentially cancerous areas; If something suspicious is found, that test is followed by more tests, often High probability of false positives, harmful and costly,

they are curvature This is the main reason why screening is limited to the highest risk groups. By adding predictive algorithms to mammograms, the risk areas of a patients breasts would be limited and the reliability of diagnosis increased to 90 percent. Therefore, they can be done with Often and the age range of the women they target Expansion,

It is a process that already exists, which uses artificial intelligenceand that . develops a team of Superior Council of Scientific Inquiry (CSIC), specifically the Institute of Corpuscular Physics (IFIC). it is part of the scope of machine learning (machine learning) in precision medicine, and a research network that seeks to increase the efficiency with which each patient is treated and optimize health care resources.

To understand how, you must first understand the concepts that come into play. The first is artificial intelligence. the ability of a computer or robot to perform tasks normally associated with intelligent beings, defined as sara degli-apostic You carlos sierra, author of the CSIC white paper on the subject. That is, they are the processes that are used replace human work with robotsWith the aim of accomplishing this with greater accuracy and greater efficiency.

And where can artificial intelligence work in medicine today? On many fronts, he replies. dolores del castilloResearchers from CSICs Center for Automation and Robotics, From the administrative to the management of clinical documentation. And, in a more specific way, in the analysis of images, or in the monitoring and follow-up of patients. And where are the still bigger limits? Above all, in the field of health care, in legal and ethical aspects when dealing with important matters. And whats more, theres still a long way to go, explains Del Castillo, who works on the projects, among others. neurological movement disorderTraining for a large section of healthcare workers.

We find the second concept as a subfield of artificial intelligence, along with its advantages and disadvantages: machine learning, This can be translated as machine learning. That is, artificial intelligence that works through computers thatand find patterns in population groups, With these patterns, predictions are made about what is most likely to happen. machine learning translate data Algorithm,

Precision medicine to predict disease

and after artificial intelligence and machine learningThere is a third concept: the precision medicine, The one that suits the person, his genes, his background, his lifestyle, his socialization. a model that must first be able predictable disease, Second, Francisco Albiol from IFIC, continues to assess each patient, apply the best treatment based on clinical evidence, identify the most complex cases, and assess their inclusion in management programs.

It makes sense high impact disease, and does not make sense for serious diseases; For example, distinguishing the flu from a cold in primary care, as the benefits will not compensate for the effort required.

The key to the use of artificial intelligence in medicine is also cost optimization, which is very important for public health. Spains population has increased from 42 to 47 million people between 2003 and 2022, that is, more than 10 percent. and from 2005 to 2022, The average age of the population has increased from 40 to 44, We are getting older and older.

Therefore, Dolores del Castillo says, the best valued projects and, therefore, likely to be funded, are those that incorporate artificial intelligence techniques to address the prevention, diagnosis and treatment of cardiovascular diseases, neurodegenerative diseases, cancer and obesity. There is also a special focus on personal and home medicine, elderly care, and new drug offerings. The need for healthcare has been heightened by our demographics, and The aim should be to reduce and simplify the challenges with technology, we tried machine learning, summarizes Albiol.

Albiol is one of the scientists who led a program to improve breast cancer detection through algorithms. He defends, like other researchers, that if we mix machine learning with precision medicine, we should be talking about 4p medicine. Which brings together four features: Predictive, personal, preventive and participatory,

Because most purists confine precision medicine to the field of patient genetics, and would not include it in the bag that takes more characteristics into account. Those who do say that we are talking about something much broader: Applied to precision medicine, machine learning allows for Analyze large amounts of very different types of data (genomic, biochemical, social, medical imaging) and model them to be able to offer together individual diagnosismore precise and thus more effective treatment, summarizes researcher Lara Loret Iglesias of the Institute of Physics of Cantabria.

Lloret is part of a network of scientists who, like Albiol or Del Castillo, are dedicated to projects on machine learning and precision medicine. One of them developed by his team, which he leads together with fellow physicist Miriam Kobo Cano, is called Branyas. It is in honor of Spains oldest woman, Maria Branyas, who managed to overcome Covid-19: she has done so at the age of 113. In this they bring together the many casuistries of more than 3,000 elderly people, much less just genetics: machine learning establish Risk profile of getting sick or dying as a result of coronavirus, We derived data from the analysis of three risk profiles: a sociodemographic, a biological and an extended biological, which will add information on issues such as aspects related to the intestinal microbiota, vaccination and immunity.

Precision Medicine, Cancer and Alzheimers

also explain this Joseph Lewis Arcosfrom the Artificial Intelligence Research Institute. common diseases There are cancer and Alzheimers linked to precision medicine, but they have stood out with the Ictus project. Launched in the middle of a pandemic (which has made things difficult, he admits), he has treated patients at Barcelonas Belwitz Hospital who suffered strokes and, after a severe and acute phase, Have become long term,

In particular, those with movement difficulty in one hand or both. made over 700 sessions In which patients have been asked to play the keyboard of the electronic piano. Then, they transferred the analysis of finger movements to the results to see what the patterns of difficulties and improvements are. And theyve gotten particularly positive feedback among users because its not only doing an exercise, but it affects a very emotional part. The goal is now to expand it to hospitals in the United Kingdom.,

and future? Dolores del Castillo replies, I believe that the challenge of artificial intelligence in medicine is to incorporate research results into daily practice in a generalized way, but always without forgetting that it is the experts who have is the last word. To do that, doctors need to be able to rely on these systems and Interact with them in the most natural and simple wayEven helping with its design.

Lara Loret believes that we have to be able to build generalizable prediction systems, that is, the efficiency of the model does not depend on unnecessary things such as which machine the data is taken in, or how the calibration is. Francisco Albiol focuses on a problem that may be in the long run must have a solutionAt present, larger hospitals are preferred in these technologies than smaller cities or towns. convenience and reduce costs It also has to do with reaching out to everyone.

While it may include statements, data or notes from health institutions or professionals, the information contained in medical writing is edited and prepared by journalists. We advise the reader to consult a health professional on any health-related questions.

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'Machine Learning' Predicts The Future With More Reliable Diagnostics - Nation World News

Rokt has partnered with Uber Technologies (NYSE:UBER) and AMC Theatres (NYSE:AMC) to help both companies make more money on their websites and mobile apps.

Rokt is an ecommerce tech company using machine learning to help tailor transactions to each shopper. The idea behind the technology is to give companies the chance to get additional revenue, find customers at scale and give extra options to existing customers by using machine learning to present offers to each shopper as theyre entering into the final stages of a transaction. The analog here would be the impulse buying section prior to a checkout line, except specifically tailored due to each consumer due to collected data.

Uber and AMC Theatres are two of the most recognized brands in the world and were extremely pleased to partner with both of them as we accelerate our growth globally. Our global partnership with Uber will support the Uber Eats internal ad network and unlock additional profitability for the company. Our partnership with AMC has already begun generating outstanding results for the company. We look forward to expanding our relationships with both of these companies in the future, said Elizabeth Buchanan, chief commercial officer of Rokt.

Rokts deal is ecommerce technology that helps customers find the full potential of every transaction to grow revenue. Existing customers include Live Nation, Groupon, Staples, Lands End, Fanatics, GoDaddy, Vistaprint and HelloFresh, but also extend out to include 2,500 other global businesses and advertisers. The company is originally from Australia, but its moved its headquarters to New York City in the United States, and has expanded out to include 19 countries across three continents.

Rokts partnership with Uber will initially launch with Uber Eats in the US, Canada, Australia and Japan, with Rokts machine learning technology driving additional revenue for Uber during the checkout experience. AMC has partnered with Rokt to drive revenue and customer lifetime value across the companys online and mobile channels.

As millions of moviegoers come to AMC each week to enjoy the unmatched entertainment of the big screen, its important that we are offering a guest experience thats personally relevant across the entire moviegoing journey. Our partnership with Rokt enables us to better personally engage our consumers and drive higher value per transaction by optimizing each online touchpoint without adding additional cost to the moviegoer, said Mark Pearson, chief strategy officer for AMC Theatres.

Rokt uses intelligence taken from five billion transactions across hundreds of ecommerce businesses to allow brands to create a tailored customer experience wherein they can control the types of offers on display to their customers. Businesses that partner with Rokt can unlock profit upwards to $0.30 per transaction through high performance techniques relevant to each individual from the moment where the customer puts the item in their digital cart to the time their payment goes through.

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Uber and AMC bring machine learning company Rokt onboard to drive revenue - Mugglehead