LOS ANGELES –Teacher Rishi Rawat has one student who is not human, but a machine. Lessons take place at a…
LOS ANGELES –
Teacher Rishi Rawat has one student who is not human, but a machine.
Lessons take place at a lab in the University of Southern California’s (USC) Clinical Science Center in Los Angeles, where Rawat teaches artificial intelligence, or AI.
To help the machine learn, Rawat feeds the computer samples of cancer cells.
“They are like a computer brain, and you can put the data into them and they will learn
AI may soon be a useful tool in health care and allow doctors to understand biology and diagnosis of disease in ways that were never humanly possible.
Doctors not going away
“Machines are not going to take the place of doctors. Computers will not treat patients, but they will help make certain decisions and look for things that the human brain can not recognize these patterns by itself, “said David Agus, USC’s professor of medicine and biomedical engineering, director at Lawrence J. Ellison Institute for Transformative Medicine, and director at the University’s Center for Applied Molecular Medicine.
Rawat is part of a team of interdisciplinary scientists at USC who are researching how AI and machine learning can identify complex patterns in cells and more accurately identify specific types of breast cancer tumors.
Once a confirmed cancerous tumor has been removed, doctors still have to treat the patient to reduce the risk of recurrence. Den type behandling afhænger af typen af kræft, og om tumoren er drevet af østrogen. For øjeblikket, patologer ville tage et tyndt stykke af væv, sætte det på en slide, og plet med farve til bedre at se cellerne.
“Hvad den patologiske skal gøre er at bestemme, hvilken procentdel af cellerne er brun og hvilken procentdel are not, “said Dan Ruderman, a physicist who is also assistant professor of research medicine at USC.
The process could take days or even longer. Scientists say artificial intelligence can do something better than just count cells. Through machine learning, it can recognize complicated patterns on how the cells are arranged, with the hope, in the near future of making a quick and more reliable diagnosis that is free of human error.
Are they disordered? Are they in a regular spacing? What’s going on exactly with the arrangement of the cells in the tissue, “described Ruderman of the types of patterns a machine can detect.
” We could do this instantaneously for almost no cost in the developing world, “Agus said. 19659007] High resolution slide scanners plus stronger computer power allows the possibility for AI to help doctors more accurately figure out the subtype of breast cancer a patient has. ” src=”https://gdb.voanews.com/E8D35371-BC85-4C32-B3E7-8316BC927A2F_w250_r0_s.jpg”/>