UK: ztracené peníze z Vašeho bankovního účtu? No, je to vaše vina

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Banky ve Velké Británii přišly loni kvůli finančním podvodům o 133,5 milionů liber a 261,5 milionů liber kvůli e-komerčním podvodům. Podle současných zákonů ve většině evropských zemí, banky pokrývaly tyto výdaje. Avšak všechno se nyní změní.

Bank of England, GCHQ a vláda berou v úvahu myšlenku, že zákazníci zaplatí účet v případě úspěšného podvodu. Samozřejmě v případě, kdy nepřijali vhodná opatření k zajištění svého účtu / karty. Vláda Velké Británie rovněž navrhuje zakázat obětem podvodu budoucí využití bankovních služeb.

Podle nové studie z UKFCMC (UK Fraud Costs Measurement Committee), Experian a PKF Littlejohn, britská ekonomika ztrácí podvodem asi 193 miliard liber ročně. Toto číslo je obrovské, ale představte si, co by se stalo, pokud by se již banky nezajímaly o své ztráty?

Pokud tato praxe bude široce přijímaná ostatními evropskými zeměmi,množství peněz ukradených z účtů klientů bank vzroste ještě více. To by znamenalo skutečný ráj pro "cardery". Samotná osoba nebude schopna přimět k vyšetřování podvodů a zločinci budou volně pobíhat.

Jen toto pondělí jsme psali o masivním výběru peněz z bankomatů v Japonsku. Představte si, že totéž se děje v Evropě, ale peníze se Vám nevrátí, protože jste zřejmě dosti nezajistili kartu nebo PIN kód.

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Coronavirus puts artificial brains to the test

doctor. Albert Hsiao and his colleagues at the UC San Diego health system had been working for 18 months on an artificial intelligence program designed to help doctors identify pneumonia on a chest X ray. When the coronavirus hit the us, They decided to see what it might do.

they quickly deployed their program, Which dots X ray images with spots of color where you should lung damage or other signs of pneumonia. It has now been rubbed into more than 6,000 breat X rays, And it's offering up some value in diagnosis, proclaimed Hsiao, The director of UCSD's augmented imaging and artificial thinking ability data analytics laboratory.

His team is on the list of around the country that has pushed AI programs into the COVID 19 crisis to perform tasks like deciding which patients face the greatest risk of complications and which can be safely channeled into lower intensity care.

The machine learning programs scroll through millions of pieces of data to detect patterns which is hard for clinicians to discern. Yet few of the algorithms have been rigorously tested against standard procedures. So while they often appear helpful, Rolling out the programs among a pandemic could be confusing to doctors and dangerous for patients, Some AI professional warn.

Topol designated a system created by Epic, A major vendor of vapor health records software, That predicts which coronavirus patients could become critically ill. Using the tool before it will be validated is "Pandemic exceptionalism, he said.

Epic said send out model had been validated with data from more 16,000 hospitalized COVID 19 patients in 21 healthcare links. No research on the tool has been published for independent scientists to assess, But at any rate, up to now "Developed to help clinicians make treatment decisions and is not a substitute for their judgment, Said randy Hickman, A software maker on Epic's cognitive computing team.

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UCSD sped up its AI imaging project, running it out in only two weeks.

Hsiao's task, With research funding from Amazon Web companies, The University of California and the nation's Science Foundation, Runs every chest X ray taken at its hospital with an AI algorithm. While no data on the execution has been published yet, Doctors report that the tool influences their clinical decision making about a third of the time, described Dr. christopher Longhurst, UCSD Health's chief guidance officer.

"outcomes to date are very encouraging, And we're not seeing any unintended issues, he explained. "Anecdotally, We're feeling like it's advantageous, Not unkind,

AI has advanced further in imaging than in other places of clinical medicine because radiological images have tons of data for algorithms to process, And more data makes the programs more attractive, Longhurst supposed.

But while AI specialists have tried to get AI to do offers like predict sepsis and acute respiratory distress researchers at Johns Hopkins University recently won a National Science Foundation grant to use it to predict heart damage in COVID 19 patients it has been easier to plug it into less risky areas such as hospital logistics.

In the big apple, Two major hospital systems are using AI enabled algorithms to assist them to decide when and how patients should move into another phase of care or be sent home.

At Mount Sinai Health arrangement, a synthetic intelligence algorithm pinpoints which patients might be ready to be discharged from the hospital within 72 hours, celebrity fad Robbie Freeman, v. p,second in command of clinical innovation at Mount Sinai.

Freeman described the AI's proposition as a "debate starter, Meant to help assist clinicians working away at patient cases decide what to do. AI isn't making the judgements.

NYU Langone Health is rolling out a similar AI model. It predicts whether a COVID 19 patient entering the hospital will suffer adverse events next four days, explained Dr. Yindalon Aphinyanaphongs, Who leads NYU Langone's predictive analytics team.

the model will be run in a four to six week trial with patients randomized into two groups: One whose doctors will have the alerts, And another whose doctors heading. The algorithm should help doctors generate a list of things that may predict whether patients are at risk for additional complications after they're admitted to the hospital, Aphinyanaphongs pointed out.

Some health systems are leery of rolling out a technology that requires clinical validation in the a pandemic. Others say they didn't need AI to handle the coronavirus.

Stanford Health Care is not using AI to manage hospitalized patients with COVID 19, said Ron Li, The center's medical informatics director for AI clinical integration. The bay area Bay Area hasn't seen the expected surge of patients who would have provided the mass of data needed to make sure AI works on a population, he explained.

Outside a healthcare facility, AI enabled risk factor modeling is being used to help health systems track patients who aren't infected with the coronavirus but might be can also be complications if they contract COVID 19.

At Scripps health and well-being, Clinicians are stratifying patients to assess their risk of getting COVID 19 and experiencing severe symptoms using a risk scoring model that considers factors like age, Chronic scenarios and recent hospital visits. When a patient scores 7 or more, A triage nurse reaches out with details about the coronavirus and may schedule an appointment.

Though emergencies provide unique the possiblility to try out advanced tools, It's essential for health systems to ensure doctors are confident with them, And to use the tools extremely, With extensive testing and validation, Topol recounted.

"anybody are in the heat of battle and overstretched, it is good to have an algorithm to support them, he explained. "We just have to make sure the algorithm and the AI tool isn't misleading, Because lives are at stake here.

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