it's a long way, and across the north sea as well. it's an incredible effort from such a small mammal. bats are pretty hardy creatures. here in the uk we have 18 species of bats, and apart from taking a bit of a break overwinter, they've got to get out there, they've got to get out there and feed. so they can withstand a bit of wind. they can withstand a bit of rain, because they're just, they're so tough. they really are olympians. if you watch bats in the wild, they are just going, going, going, fighting for it, really, really tough competitors. so i'm sure that this particular bat just thought, "what, heathrow to moscow? no problem, sunshine." and off it went. there is a huge amount that bats can teach us. for starters, it's only relatively recently that we recognised the nathusius is a different type of pipistrelle. we used to think that they only

came to the uk to feed, and that they then went back to europe. but we now know we have breeding colonies here in the south—east, so we're always learning more and more and more. and when you consider bats really are top predators for flying insects, and flying insects themselves are an incredible indicator of environmental health and technological health. you know, you've got to have those little midges and flies pollinating our seeds and grasses and all that kind of stuff. they're an amazing keystone species, so knowing where they started, where they're going and what they might encounter on the way gives us more opportunity to protect them, look after them and in doing so, get an idea of the current state of health of our own ecosystem. now it's time for a look at the weather with tomasz. hello. not much change or a day

with a front for today and tomorrow. a lot of cloud, gusty winds in places. scattered downpours across the uk, particularly northern parts of the country, they are likely to continue into the evening hours, through to sunday and into monday as well. quite a cool picture across the uk. low pressure on top of us is slow—moving, gradually moving to the east and the north—east. the weather that it brings sits on top of the country for a considerable amount of time. through the afternoon, showers continue, particularly heavy across northern parts of the uk, maybe fewer for a time for the south of wales and devon, could be decent sunshine in plymouth. hello. this is bbc news with shaun ley. the headlines.

gold medal number 20 for team gb asjoe choong takes top spot in the men's modern pentathlon. there's a bronze forjosh kerr in the men's 1,500 metres — britain's first medal in the event since 1988. boxing gold for galal yafai — as he wins in the flyweight division for team gb. success in the pool, too. tom daley earning bronze in the 10 metre platform diving — his second medal of the games. in afghanistan, the taliban say they've captured their second provinincial capital in 2a hours. britain and the us warn their citizens to leave the country immediately. a volunteer firefighter has died as wildfires spread across greece, with thousands being moved from their homes to the north of athens. and the tiny bat who beat records by flying more than 1,200 miles across europe. now on bbc news. click looks at how artificial

intelligence could be used to help health services around the world. this week: a special programme. can artificial intelligence make healthcare better for all of us, and save the nhs? here in the uk the national health service has been in crisis for many years, looking after an increasingly ageing population with complex needs. fighting for resources, it has been at breaking point. and then the pandemic hit. there will come a moment when no

health service in the world could possibly cope. and indeed, many countries�* health systems have struggled with the sheer number of covid patients. even those which didn't have people spilling out onto the streets had to put all other treatments on hold. the nhs is an old health system. in fact, it's several different systems that sometimes work together and sometimes don't. and now, it's trying to reinvent itself and embrace technology to beat the queues that covid—19 has created. this is a story i started filming just before the first uk lockdown, when we weren't yet wise to masks or social distancing, but there was definitely a hint that something was coming. i wanted to find out how artificial intelligence could be used to help take up the strain that the nhs was already under. and, on what turned out to be my last day in london for many months,

i found myself about to do something that i'd never done before. i wasn't nervous until i asked my twitter followers what i can expect. "very loud noise — claustrophobia." now i'm nervous. i'm going to have an mri scan on my liver. and i have to lay absolutely still? yep, and there's breathing instructions. this magnetic resonance imaging scanner — mri scanner — is going to be able to see my soft tissue and my fluid in great detail. and it will produce images like this, which will be looked at by a radiologist to try and work out if they can see anything unusual. now, the thing produces really strong magnetic fields, which means nothing metal can come in — and that includes you. but this is no ordinary mri scan. instead of being read by a human, my mri is going to be read by an artificial intelligence. this is a computer that will look at the images

and read them at least as well as a human radiologist would. breathe out and hold your breath. now, this film is not about computers stealing jobs. this is a film about computers filling the gaps in an nhs that is short of money, short of nurses, and short of the highly skilled radiologists who can read and interpret images like these. but that's a really difficultjob that takes years of training. i mean, how could you teach a computer to do that? well, here's a classroom full of medical students, and this is a computer. the way you teach each is very different. what you have in front of you here are ct scans of a human lung with cancerous tumours. so i'll be teaching you how to identify them

and hopefully save lives. the human brain is brilliant at learning things. it can understand spoken words. it can understand diagrams. just through the teacher's descriptions, these students can have a good guess at finding tumours in these images. they get some right, they get some wrong. but with repetition and practice, their brains make more and more connections — which strengthen with success until eventually we really understand the task in front of us, and we can do it well. but computers are dumb. they literally know nothing. they can't look at a diagram and imagine it in real life. they can't understand spoken words.

normal teaching methods won't work. so, instead of trying to describe to them what we want them to learn, we teach them using trial and error. millions of trials, in fact. the computer starts by circling completely random parts of the image. itjust guesses — it doesn't even know what it's guessing at. all it knows is when its guess is right and when it's wrong. and mostly, because it's guessing, it's going to get it wrong. and the great thing about computers is they can do this over and over again, really fast, and they remember everything. and every time it does accidentally get it right, it makes a connection to its previous correct guesses.

with every right answer, certain connections get stronger. and with every wrong answer, others get weaker. through this barrage of guesses a network grows, similar to the human brain, which starts to distinguish between right and wrong. a digital thought process that we call a neural network. until eventually, after a multitude of attempts, it has very few failures and a lot of success. ok, let's try some more difficult scans now. so if we just take your gown off... and this is the technique that could soon help to relieve the pressure on the uk's breast screening service.

almost 1000 women die from breast cancer in the uk every month. the aim is to catch the disease early when it's most treatable. but that means that more than 2 million women have their breasts scanned for potential cancer every year. my entire role is clinical diagnostics within breast. you know, it takes up a great deal of my life, it is really important, and we are kind of fighting a big fight. bernadette works at the lincolnshire breast screening service, and she is part of a shrinking workforce. for years, the nhs has been unable to train or even recruit enough radiologists, and many services now face chronic staff shortages. this is further complicated by the fact that each mammogram needs to be read independently by at least two specialist clinicians.

so we have two people reading a mammogram, because it is actually a really difficult process, 0k? what looking for is tiny, tiny cancers. maybe two millimetres, maybe a little tiny smudge within a breast. and we are human, and some of us miss them. so that second read is that second opportunity to pick up that tiny little smudge that may, you know, change a woman's life. so the nottingham university hospital has been trialling a new tool that may help. this is mia, an ai trained to spot breast cancer. the aim of this project is for this system to be the second reader, potentially speeding up the whole process. so mia has had a look at this mammogram as well, can we have a look at what mia thinks? so in this particular case, mia has actually marked

the area that i would also be concerned about. and it makes a callback decision itself and as you can see there mia says callback, malignancy, because it's suspicious. its makers, kheiron medical, have been developing mia for over 3 years. here in nottingham, jonathan and his team have been testing mia on the hospital's historical data sets. these are scans from women who have been to this clinic in the past and were diagnosed by a human. the aim is to see if mia would have made the same decisions. so this time, mia hasn't actually placed any mark on the image here, and its opinion is no recall is required. actually this lady did come back for some extra tests and this well—defined mass, she had an ultrasound when she came back and this was a cyst, a perfectly harmless cyst. so i suppose the recall would be a false positive, this lady didn't actually need to come back. a false positive is when the reader thinks that there is cancer, but on further investigation it

turns out that they were wrong. and over at the cambridge breast unit, professor fiona gilbert has been conducting research to try and reduce those false positives. something that not only put a lot of strain on the system, but also a lot of strain on the patients. it is obviously causes quite a lot of distress to the woman being called back, and the majority of them turn out to be normal. it's a lot of work for us to be assessing all of these women for a relatively small number of cancers. and when a programme screens over 2 million people every year, these little percentages do matter. every year around 70,000 women are given a false positive result, and some never attend a screening again. fiona and her team have been testing an ai built by google health to see how the software compares to human radiologists. so in the retrospective study that was done,

the algorithm performed better than some of the individual radiologists, and worse than other radiologists. so when they took the average performance of all the radiologists, the algorithm would have called back fewer people. but this research project is still in its early stages, and is set to move to the next phase of development this year. in the meantime, back in nottingham, mia has finished its initial trials and will now be tested in 15 more nhs sites against ongoing cases, to make sure that it works. artificial intelligence is the next amazing transformation, so that is what excites me. and it excites me that i don't know the full potential. we know that the cancers we are missing tend to be smaller, they tend to be more aggressive, and those are the ones that we want to find. but as the pandemic hit, all of this had to stop.

and as breast clinics emptied out, elsewhere the nhs was about to be overrun. the coronavirus pushed intensive care units beyond their limit. but even before the pandemic, these wards had been running at very near capacity. and it is here that one of the biggest killers in the uk, and indeed the world, lurks. it is called sepsis. so sepsis is when there is a severe infection, and when the body's response to that severe infection leads to organ failure. it can set in without warning, and can affect anyone. this is a lady in her early 50s, she is in day four on the unit, she was very unwell initially. people are admitted to icus for many reasons, but sepsis tends to strike when patients are at their weakest. we literally collect every

heartbeat and every breath. when you first start in intensive care, when i started, it was difficult to see what was important because there was much data. but remember, computers love data, and love spotting patterns in it. they don't get tired, and they never stop. so the doctors and computer scientists teamed up to create something called ai clinician, an algorithm that can detect and even predict early signs of sepsis, and then advise how to stop it. what we have used is a large database with 20,000 patients, and then we tested it in another 80,000 patients. that's more than any doctor could see in their lifetime. the trials were proving successful, but neither the al or the humans were ready for a new type of sepsis, one brought on by covid—19.

there are a few differences. one is the intense inflammation they had in the lung made the oxygen levels really low, and so they needed high amounts of oxygen. if they didn't tire of their breathing so quickly as many patients with other pneumonia often struggle with their breathing. we also saw things like a lot of blood clots, which we occasionally see in other sepsis, but were far more frequent in this disease. nearly all the patients coming through to icu now have this new sepsis, and for the ai, this was an illness it had never seen before, nor had any data on. and remember, just because a computer has learned to be good at one task, doesn't mean it can do a different one. the ai clinician was back to square one.

but the humans weren't. their idea was to gather data from icus across the uk to create a database of treatments that worked, so the doctors in the thick of it could learn from each other at speed and save their patients. we build for the first time a picture of how disease was treated in real—time on the databases across the country. and you see all see the diversity of all the different approaches people are trying, what was working and what was not working. now this data will be used to retrain ai clinician and one day it may help to treat sepsis that's caused by covid. so it's about 18 months since we started making this programme and in that time we've all started to use technology in new ways and some of that has included gp consultations over video call, for example. so i think it probably means that many of us will be happy to accept medical help from machines and computers in the future. but for those computers to be good at theirjobs, they are going to need a lot of data.

a lot of our personal medical data. many services like instagram, google and facebook don't charge us any money. instead they get to use our personal data to try and work out how better to target us with ads. for many of us, that seems like a fair exchange. they make our lives easier and they connect us to the world. but now, those same companies which have been collecting and profiting from our personal data are moving into healthcare. amazon, microsoft and google are all trying to grab a seat at the table and dine on our medical data. and the nhs has something unique to offer. a whole nation's information

from birth to death. that's something that might make one feel uncomfortable. i don't think many health professionals sit down with their patients and say do you want your data to be sold to google or deep mined? i don't think those kind of conversations are being had. we're notjust talking about the big household tech names either. plenty of other companies that you never have heard of also want access too. the issue of sale of data to technology companies is an interesting and controversial issue. there are some people who believe it's an asset to the nhs and we should sell it, there are other people who believe that in some way or another that's a wrong thing to do from a moral point of view. but if we get it right — and it is a big if — the benefits could be huge. a unified joined—up store of medical data could really speed up research and lead to new treatments.

and ai would be used to look for the patterns hidden within. and that's something that could soon be helping those who are suffering from long covid. thanks to artificial intelligence, we were able to link patient records with imaging and produce an analysis of 41,000 patients, imaging and clinical associations in about two months. adriana roca is part of a team that has been looking into why long covid only affects some people. what we found was quite important and shocking because it was actually not obesity, per se, but fatty liver disease linked to obesity that was increasing the risk actually up to five times of being severe with covid—19. ajay agade is one of almost a million people suffering from long covid in the uk. he's a0 and a doctor, and he moved to the uk from india to complete his specialist training.

so in the last week of march i was on the weekend duties and i was not feeling well. i went back home immediately. i self—isolated and then i was tested positive. i wasn't thinking that this virus will affect me because i was a fit adult and i thought it would be just ok, like any other flu virus is for me. there was a moment when i thought iwilljust die, and i had a three—year—old, and i would not be able to see her ever in my life. i never knew that this virus will leave me or others with so many problems and disabilities, even after one year. so, to understand his illness more, ajay signed up to a study aiming to help long covid patients — a trial that's using the very same ai that lured me into that big magnetic tube earlier.

this ai had originally taught itself how to spot certain liver characteristics. as well as spotting unusual masses, it had also learned to assess the overall health of the liver. and here's what made of mine. here we've picked up a small area which isjust a cyst, a simple fluid—filled sac. and the ai has picked that up as something unusual, something of interest? yes, but there's no concerning features to it and we wouldn't survey it. and otherwise it's a reassuring scan, with no increased evidence of inflammation or scarring, iron or increased risk of fat. but here's the thing. it turns out that because this ai can assess the overall health of the liver, it can do the same for other organs too. and so we expanded first to organs like the kidneys the pancreas, the spleen and the heart, originally with the aim of looking at type 2 diabetes, but it turned out that a lot of those organs were being affected by covid as well.

if it was a radiographer manually analysing data from, say, six different organs, that could be up to about 24 man—hours of work. this allows us to basically automate some of the most labour—intensive parts of the process. we are trying to identify. which kind of fat is the one that puts you at risk. it's not obesity, as we've thought up until now. - what makes you at higher risk is the visceral fat, _ the fat in the organs. whereas we have found. also people with low bmi with high fat in the liver. ajay is part of the clinical trial which may show that young, fit people with a normal bmi can also get long covid if they have fat in their organs. and not everyone is aware about exactly what long covid is. i think eventually when the acute things wean off, i think more

and more people will come out with long covid. there are many trials in the country trying to understand long covid, and artificial intelligence has become a big tool in the race to find a treatment. but for many, help can't come quick enough. technologies that bring about big change also bring new problems. there is no point in denying that. but right now, ai is changing the world and opening up possibilities for huge medical breakthroughs. i mean, it helped us to develop highly effective vaccines in record time. so i know the pandemic is far from over, but i still feel kind of lucky that it happened now rather than even just a decade ago. and maybe it will mean the nhs is a bit more ready for the next one.

it is a classic mixed bag today, changing from hour to hour and minute to minute across parts of the country, sunny spells and heavy downpours, cracks of thunder, and all brought along by this low pressure sitting over the top of us. it will be here today, tomorrow and be influencing us on monday as well. there is a lot of cloud across the uk with a few breaks here and there, but overall quite a cloudy picture and you can see the distribution of showers. end of the afternoon, really heavy ones across parts of scotland, northern england and northern ireland. in the south there are still

some heavy ones around, but they still come and go, and the chance of a bit more brightness and also in the north—east of scotland here, not a bad day overall. so there are pockets of decent weather. here is the low pressure through the night, you can see spinning away on top of us. this is a slow—moving area of low pressure, spinning over is quite fast, but it is moving slowly, so the weather it brings sits over the uk for quite some time, and here it is again on sunday, in fact the centre has hardly moved. it has only drifted ever so slightly towards the north. that also means that the wind on the southern flank will be a little stronger across parts of england and wales, really quite gusty, a0 mph gusts. that might be a decent thing because it means any heavy showers will be blown through quite quickly. lighter winds will be across northern areas so here the showers will be slower moving, heavy showers more prolonged. temperatures are quite disappointing with all of this, not much change into monday, a scattering of heavy showers once again.

there are hints that things are going to improve. from around tuesday to wednesday and thursday, we will be in between weather systems, there is more low pressure in the atlantic that this little bump of high pressure builds in, it is only a weak area, and it suggests that they will be slightly warmer area coming from the south, but mostly affecting south—eastern and eastern parts of the country, not super warm but warmer compared to what we have got right now. you can see the gentle rise, temperatures could hit 2a or 25 degrees in the south—east, so that is something. goodbye.

this is bbc news — the headlines at four. gold medal number 20 for team gb — asjoe choong takes top spot in the men's modern pentathlon. there's a bronze forjosh kerr in the men's 1500 metres — britain's first medal in the event since 1988. boxing gold for galal yafai — as he wins in the flyweight division for team gb. success in the pool, too. tom daley earning bronze in the 10 metre platform diving — his second medal of the games. in afghanistan, the taliban say they've captured their second provincial capital in 2a hours. britain and the us warn their citizens to leave the country immediately. we are extremely concerned about the safety and security of people in cities under taliban

attacks and what brutality would await them.