at the moment its like feeding ai images of parrots and then giving it a 50-50 example of parrots vs humans and it being 99% predictable. but the fed in images of parrots where only one breed of parrot. so the occassional other bread dont get recognised as a parrot.
eventually AI will be fed more info and become more accurate. all it just needs is more info
this AI technique is not new.
back in my child hood i had a games system that used a device called a 'game shark cheat code system' what it basically done was get you to perform a series of tasks where one element stays the same and a series of tasks where just the element changed. and it worked out the memory area that was sensative to that element. so that if you changed the memory locations data you changed the element. thus able to get unlimited lives or unlimited ammo.
AI does the same thing. if you give it enough info of negative and positives it can work out the element it needs to concentrate on. the more data its given the more accurate it gets
things can move alot faster by comparing blood results too to find similar characteristics of certain enzymes to know if someone is at risk of something.
same with DNA. feed it enough dna where a known characteristic is known it can then identify where that characteristic exists in the dna. thus then able to identify characteristics when supplied a fresh sample with no pre-briefed characteristics
things will get better and faster and not reqire human eyes needing to look at scans. but just getting the answer as soon as the sample is scanned
Topic: In the Fight Against Cancer, AI is Winning – sometimes (Read 135 times)
Researchers from Google, Northwestern University, the NHS, and Imperial College London have discovered that Google’s Deepmind AI outperforms radiologists in detecting breast cancer. The researchers trained the AI on thousands of mammograms, which resulted in the tech being able to identify breast cancer cases better than the radiologists who had made the initial assessment. In the fight against cancer, AI is winning - sometimes.
https://www.youtube.com/watch?v=Nj2YSLPn6OY&t=4s
The Study
When analysing 18,000 patients from the US, the research showed that there was a 5.7% reduction in false positives, and a 9.4% reduction in false negatives. In the UK, the data showed a 1.2% reduction in false positives, and false negatives reduced by 2.7%. The researchers had a much bigger database to work from in the UK, screening more than 100,000 patients.
The researchers then pitted the AI system against a group of six highly skilled radiologists. They were tasked with interpreting 500 cases, all randomly selected. Here the AI outperformed the radiologists too, however it did miss some cases that the team had highlighted as positive for cancer. So, in the fight against cancer, AI is winning - sometimes.
As the study’s abstract notes, the system is “...…capable of surpassing human experts in breast cancer prediction.” However, it’s unlikely that AI will replace human radiologists in the field anytime soon.
Machine learning algorithms are more than capable at completing repetitive tasks (like going over thousands of x-rays), it’s not quite ready to start popping up in hospitals and clinics.
https://www.youtube.com/watch?v=ik9ps7L-p2E
According to Dr Hugh Harvey, managing director of digital health consulting firm, Haridan Health, “AI is perfect to support breast cancer screening. Machines are perfect for doing mundane, high-volume tasks.” He continued, “All of this early research is all well and good. To actually get it deployed into the clinic is a whole lot of work.”
An AI system will also still need to be approved by the FDA, and would likely have to connect with a hospital’s health records, and would need constant surveillance (human or otherwise) to ensure that its findings are maintaining their accuracy.
Will it be implemented?
Frankly, the study does have its limitations. Yes, researchers had a large and diverse data set, but all of the images were from a single manufacturer’s mammography system. The actual demographics of the study (as in the patients) was also not too diverse, and the study should have used a better variety of the population to enable any real accuracy. This technology will also have to be tested in clinical trials before it’s ever implemented.
“The real world is more complicated and potentially more diverse than the type of controlled research environment reported in this study,” wrote Dr. Etta Pisano, chief research officer for the American College of Radiology, in an analysis of the research. She added that earlier versions of this technology, like computer-aided cancer detection, showed good initial results. But when it came to real-world application, the systems just weren’t up to scratch.
Still, what benefits can this tech have? Can it reduce patient mortality, or make radiologists more efficient? Will it reduce costs? So far, it looks promising, but we haven’t seen anything concrete.
“Those are the papers we’ll see in the next couple of years,” Harvey noted. “The only industry we can look at to give us an estimate of how long (approval) takes is the pharmaceutical industry. People predict the digital sector will go faster, but we still have to do these prospective studies.”
https://twitter.com/DeepMindAI/status/1212456717306540033
It won’t be in the field anytime soon
While this report is very promising, the actual technology won’t be in the field anytime soon. Yes, in the fight against cancer, AI is winning - sometimes. But, really, only sometimes. Will this technology have enough real world benefits to pass clinical trials, or will it never see the daylight. AI has the power to change lives, and save lives, but we’ll never see this project come to fruition unless they expand on their research. Still, this research has certainly highlighted one important thing - there’s nowhere AI can’t reach.
https://4king.com/ai-is-winning-sometimes/
https://www.youtube.com/watch?v=Nj2YSLPn6OY&t=4s
The Study
When analysing 18,000 patients from the US, the research showed that there was a 5.7% reduction in false positives, and a 9.4% reduction in false negatives. In the UK, the data showed a 1.2% reduction in false positives, and false negatives reduced by 2.7%. The researchers had a much bigger database to work from in the UK, screening more than 100,000 patients.
The researchers then pitted the AI system against a group of six highly skilled radiologists. They were tasked with interpreting 500 cases, all randomly selected. Here the AI outperformed the radiologists too, however it did miss some cases that the team had highlighted as positive for cancer. So, in the fight against cancer, AI is winning - sometimes.
As the study’s abstract notes, the system is “...…capable of surpassing human experts in breast cancer prediction.” However, it’s unlikely that AI will replace human radiologists in the field anytime soon.
Machine learning algorithms are more than capable at completing repetitive tasks (like going over thousands of x-rays), it’s not quite ready to start popping up in hospitals and clinics.
https://www.youtube.com/watch?v=ik9ps7L-p2E
According to Dr Hugh Harvey, managing director of digital health consulting firm, Haridan Health, “AI is perfect to support breast cancer screening. Machines are perfect for doing mundane, high-volume tasks.” He continued, “All of this early research is all well and good. To actually get it deployed into the clinic is a whole lot of work.”
An AI system will also still need to be approved by the FDA, and would likely have to connect with a hospital’s health records, and would need constant surveillance (human or otherwise) to ensure that its findings are maintaining their accuracy.
Will it be implemented?
Frankly, the study does have its limitations. Yes, researchers had a large and diverse data set, but all of the images were from a single manufacturer’s mammography system. The actual demographics of the study (as in the patients) was also not too diverse, and the study should have used a better variety of the population to enable any real accuracy. This technology will also have to be tested in clinical trials before it’s ever implemented.
“The real world is more complicated and potentially more diverse than the type of controlled research environment reported in this study,” wrote Dr. Etta Pisano, chief research officer for the American College of Radiology, in an analysis of the research. She added that earlier versions of this technology, like computer-aided cancer detection, showed good initial results. But when it came to real-world application, the systems just weren’t up to scratch.
Still, what benefits can this tech have? Can it reduce patient mortality, or make radiologists more efficient? Will it reduce costs? So far, it looks promising, but we haven’t seen anything concrete.
“Those are the papers we’ll see in the next couple of years,” Harvey noted. “The only industry we can look at to give us an estimate of how long (approval) takes is the pharmaceutical industry. People predict the digital sector will go faster, but we still have to do these prospective studies.”
https://twitter.com/DeepMindAI/status/1212456717306540033
It won’t be in the field anytime soon
While this report is very promising, the actual technology won’t be in the field anytime soon. Yes, in the fight against cancer, AI is winning - sometimes. But, really, only sometimes. Will this technology have enough real world benefits to pass clinical trials, or will it never see the daylight. AI has the power to change lives, and save lives, but we’ll never see this project come to fruition unless they expand on their research. Still, this research has certainly highlighted one important thing - there’s nowhere AI can’t reach.
https://4king.com/ai-is-winning-sometimes/
Jump to: