Wallabies chasing more accuracy for win


Wallabies attack coach Scott Wisemantel says Australia need to bring their A-game against New Zealand on Saturday, demanding accuracy as they attempt to level the Bledisloe Cup series.

Missed tackles and turnovers by the Wallabies were costly in the 27-7 loss in the second Test in Auckland and Wisemantel wants to see better in the ANZ Stadium clash.

“We just need to be far more accurate,” Wisemantel said.

Asked for more specifics the coach replied: “Where do you want to go? Defence, attack? Our whole all-round game we’ve got to be more accurate, that’s it.

“We spoke about accuracy and we’ve got to get that right.”

Wisemantel helped England head coach Eddie Jones orchestrate a win over New Zealand in last year’s World Cup semi-final so knows what it takes to knock them over.

He said the Australians had the right mindset but were let down by their execution.

However, he was adamant there wasn’t a “drop-off”.

“There wasn’t a drop-off,” Wisemantel said.

“The intensity, the intent was good. You saw the intent. We went out there to score tries, we went out there to smash them.

“The problem was we didn’t control the game and were inaccurate and that’s what cost us.

“If you’re inaccurate against New Zealand, who many say are the best team in the world, then you get punished and that’s what happened.”

The Wallabies will have a new inside centre following Matt Toomua’s groin injury but Wisemantel felt they would be well-covered in the absence of the veteran.

Brumbies back Irae Simone could get his Test debut or Hunter Paisami, who shifted there in Auckland after Toomua left the field, may also wear the No.12 jersey.

“Irae deserves to be in the squad on the back of his performances with the Brumbies,” he said.

“His evolution is a slow burn … he’s changed a few things about himself and was in a great system with the Brumbies and that culmination of two things was a tipping point.”

Among other changes with the team to be named Thursday, veteran fullback Dane Haylett-Petty and exciting outside centre Jordan Petaia could come into the starting side.

“When you look at that attacking shape we can chop and change within that and that’s the beauty of the system that we’re playing,” he said.

“Whoever jumps into that role, we expect them to do the job and do it well, with good skill.”





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Eric Hipwood calls for greater accuracy from Brisbane Lions


Lions forward Eric Hipwood admits Brisbane’s goal-kicking skills remain a work in progress but is confident the worst is over.

Brisbane’s poor conversion rate has been a problem for most of the season and probably cost them the minor premiership considering they finished on the same points as first-placed Port Adelaide only to be nudged into second spot on percentage.

In 17 regular season matches, the Lions kicked 165 goals and 194 behinds.

It’s the most behinds kicked by any team this season.

“I looked at it as a positive thing that we were getting so many shots – we just weren’t converting them,” Hipwood said.

But signs of accuracy improvement have been evident in the Lions’ past three games, in which they have kicked 35 goals compared to 29 behinds.

“We knew it was going to take a while and we’re starting to reap the benefits, but yet again it can change pretty quickly so we’ve got to keep honing down on our skill and continue our improvement,” Hipwood said.

“It’s been a marginal gain for us, and we seem to be improving a little bit but we can’t stop now. We’ve got to be improving on our goalkicking.”

https://twitter.com/brisbanelions/status/1308266204486750208

Hipwood, who regular season goal accuracy of 45.1 per cent was below AFL average, was adamant the constant focus on Brisbane’s goal-kicking problems this season had not played on the Lions’ minds.

“It doesn’t affect us at all. We’ve just got to listen to the people within our four walls,” he said.

“There’s obviously going to be some sort of scrutiny on us no matter how well we’re going.

“I was always very optimistic and it didn’t faze me too much.

“It just takes a while for things to come.”

A lack of accuracy also cost the Lions dearly in their qualifying final loss to Richmond last season.

The Tigers won 18.4 (112) to 8.17 (65) at the Gabba to send the Lions into a sudden-death semi-final a week later that they lost to the GWS Giants.

Brisbane again host Richmond in a qualifying final on Friday week, with Hipwood confident of a different outcome despite the Lions have not beaten the Tigers since 2009.

“We’ll look at teams that have beaten them and we’ve analysed them a fair bit,” he said.

“They’re a quality side and we’re going to have to be at our best to match it with them.

“I treat every game like it’s our last. That’s my mental approach to it and I don’t think too much will change.”





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Artificial intelligence diagnoses Alzheimer’s with more than 95% accuracy


  • A team from Stevens Institute of Technology has developed an artificial intelligence (AI) tool that can diagnose Alzheimer’s disease with more than 95% accuracy
  • Researchers expect providers can use the AI tool to diagnose Alzheimer’s more accurately for earlier treatment and reduced healthcare costs
  • The AI algorithm enables human experts to check for accuracy and explain their conclusions

An artificial intelligence (AI) algorithm has produced another significant breakthrough using attention mechanisms and a convolutional neural network to accurately identify tell-tale signs of Alzheimer’s.

The AI tool developed by the Stevens Institute of Technology is said to be able to explain its conclusions, thus enabling human experts to check the accuracy of its diagnosis by up to 95%.

AI has made huge strides in the medical sector and this latest news is further evidence that the speed at which the technology is moving shows no signs of ceasing any time soon.

The algorithm is trained to identify subtle linguistic patterns previously overlooked by using texts composed by both healthy subjects and known Alzheimer’s sufferers. The team of researchers then converted each sentence into a unique numerical sequence, or vector, representing a specific point in a 512-dimensional space.

The method conducted by the team allows complex sentences to be assigned a concrete numerical value and is said to analyze structural and thematic relationships between sentences simpler.

The AI algorithm gradually learns to spot differences between sentences composed by either the healthy or unhealthy individuals before determining precisely how likely any given text was to have been produced by someone with Alzheimer’s.

The news is a huge step forward for AI in healthcare and unlocks a plethora of new possibilities and potential for the future.

“We’re opening an exciting new field of research, and making it far easier to explain to patients why the AI came to the conclusion that it did while diagnosing patients. This addresses the important question of trustability of AI systems in the medical field”, said creator and founding director of Stevens Institute of Artificial Intelligence and professor of electrical and computer engineering at the Charles V.Schaefer School of Engineering & Science, K.P. Subbalakshmi.

Besides the system’s significant accuracy, the AI algorithm is also capable of incorporating new criteria established by other research teams in the future.

“We designed our system to be both modular and transparent, if other researchers identify new markers of Alzheimer’s, we can simply plug those into our architecture to generate even better results”, explained Subbalakshmi.

New opportunities

On a theoretical level at least, the latest developments mean that AI systems could one day diagnose Alzheimer’s based on any text such as email or a social media post. The algorithm, however, would first need to be trained using a wide variety of texts produced by Alzheimer’s sufferers, instead of just picture descriptions. At the date of writing, that kind of data just isn’t available yet.

Subbalakshmi went on to add, “The algorithm itself is incredibly powerful, we’re only constrained by the data available to us.”

The researchers will be moving forward by gathering new data to help the algorithm diagnose patients with the disease based on speech in languages other than just English. Beyond that, the team hopes to discover how neurological conditions like stroke, aphasia, traumatic brain injuries, and depression can impact the use of language.

Prior research conducted by the University of Sheffield’s Neuroscience Institute this year has already examined how the use of AI regularly could help relieve the time and economic impact common neurodegenerative diseases like motor neurone disease (MND) and Parkinson’s.

“Most neurodegenerative diseases still do not have a cure and in many cases are diagnosed late due to their molecular complexity”, said lead author of the study, Dr. Laura Ferraiuolo from the University of Sheffield.

With populations around the world living longer than ever before, the number of people with neurodegenerative diseases is expected to hit unprecedented levels. By 2050, the number of people living with Alzheimer’s is predicted to treble to 115 million, posing a serious threat to health systems globally.

As advances in AI algorithms continue to show signs of promise, the boundless potential for where the technology could take the healthcare industry is intriguing.





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AFL 2020: AFL ladder, champion data, expected scores ladder, ladder predictor, goalkicking accuracy ladder


Fox Footy analysts David King and Leigh Montagna have drawn attention to Champion Data’s ‘expected scores ladder’ in trying to make sense of where teams really stand heading into the final stretch of the home and away season.

Speaking on Fox Footy’s First Crack, the pair explained what the metric does and why some clubs take more notice of it than other key indicators.

“It’s an audit of your offensive and defensive systems sans accuracy,” King said.

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Ascertain accuracy of rapid antigen tests: Government to ICMR | India News


NEW DELHI: The government has asked ICMR to evaluate the accuracy of rapid antigen testing (RAT) in detecting coronavirus through mathematical modelling and analyse if the proportion of false negatives is substantially high, as has been suspected in some instances, official sources said.
“We have asked ICMR to check the accuracy level mathematically by assessing how many samples are symptomatic but report negative in rapid antigen tests and then what is the average percentage which turn out positive on a repeat test with RT-PCR. This has to be assessed on samples from across the country. If there are concerns, they need redressal. Once it is done , we can be assured that our numbers are correct,” a senior official told TOI.
While use of antigen tests helped ramp up testing significantly across the country, false negatives and missing repeat tests to confirm through RT-PCR has led to concerns that this might lead to wider spread. The tests need to be conducted carefully and also the RT-PCR testing of persons with symptoms who test negatively has to be done scrupulously.

“It is well recognised that antigen tests have a lower sensitivity than RT-PCR tests which themselves have a modest sensitivity of around 60%. So, antigen tests by themselves are likely to miss more than half of the Covid-19 infected cases. Wherever there is strong suspicion on grounds of clinical features or contact history, RT-PCR must be performed for antigen negative cases. If clinical features are strongly indicative, even a negative RT-PCR test should not dissuade from treating the person as a Covid-19 case,” says Public Health Foundation of India (PHFI) president K Srinath Reddy.
According to ICMR’s protocol, any sample testing negative through RAT will have to be mandatorily retested with RT-PCR if the person demonstrates symptoms. Those testing negative with no symptoms are to be monitored for a few days. If they develop symptoms then they are to undergo RT-PCR testing too.
In Delhi, 15% of symptomatic individuals who tested negative in RAT were found to be positive in a second confirmatory RT-PCR test. The total number of such persons tested was however less than 3,000. The total tested by the RAT method was close to 3 lakh.
India has been testing more than 5 lakh samples in a single day to check Covid-19 over two consecutive days. Cumulatively, India has so far tested more than 1.73 crore samples. The tests per million stands at 12,562.



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