Clinical Professor of Radiology at the College of Human Medicine, Michigan State University, Mukkamala Apparao, speaking at the national conference of Indian Radiologists and Imaging Association in Mangalagiri on Thursday.
| Photo Credit: G.N. Rao
Application of Artificial Intelligence (AI) in radiology will help in faster, better and more accurate detection of certain types of cancer, said Mukkamala Apparao, radiologist and clinical professor of radiology at the College of Human Medicine, Michigan State University.
Speaking on the sidelines of the national conference of Indian Radiologists and Imaging Association in Mangalagiri on January 25 (Thursday), Dr. Apparao said: “AI will detect cancers present in the smallest parts of the body, which a human eye may not detect easily. Except blood cancer, it can detect cancers of breast, lungs, cervical, prostrate, brain in the early stage. Early detection of cancers will have 90% recovery rate.”
“In the future, a radiologist who has knowledge of AI may replace a radiologist without any knowledge of AI. While AI alone may not be enough, the combination of man and machine can do better,” Dr. Apparao, also the founder of the Telugu Association of North America and the American Association of Physicians from India, said.
“In our country, we can make use of AI in tribal areas where the strength of medical professionals is weak. Today, while the growth rate of radiology is around 8%, the growth rate of radiologists in India is hovering around 3%. We need AI to fill this gap,” he said, adding that the technology, however, may gain popularity only after 20 years.
Also, the present algorithms are designed for the American population, and there is a need to develop a new algorithm that suits Indians, he said.
He said that experts in the field are having discussions on whether a patient should be charged more if the consulting doctor is using AI. “We are beginning with built-in AI in CT and MRI scanners in the country,” he said, concluding that application of AI will bring in a lot of positive changes in the field of radiology.