A new doctor has been stationed in the examination room and has no name yet. In fact, these doctors don't even have a face. Artificial intelligence has entered hospitals around the world. There is nothing to worry about for those who are wary of robotic acquisitions; the use of artificial intelligence in health care does not necessarily lead to conflicts between human thinking and machines. Artificial intelligence expands and strengthens in the examination room, sometimes relieving the nervous nerves of the doctor, so that the doctor can better serve the patient. Bertalan Meskó, known as the “Future Medical Scientist,†regards artificial intelligence as a “21st Century Stethoscopeâ€. His assessment may be more accurate than expected. While various techniques and tests provide them with all the information they need to diagnose and treat patients, doctors have already overburdened clinical and administrative responsibilities, and categorizing the vast amount of information available is a daunting task, almost no Possible tasks. This is the meaning of the existence of a stethoscope in the 21st century. Despite this, the application of artificial intelligence in medicine has gone beyond the scope of administrative management. From powerful diagnostic algorithms to well-designed surgical robots, this technology is well known in the medical world. Obviously, AI has a place in medicine, and we don't know its value. Imagine that artificial intelligence is part of the patient care team, and we must first understand better how artificial intelligence reaches the level of human physicians. How to compare accuracy? What specific or unique contribution can AI make? Is artificial intelligence very helpful in medical practice, or even harmful? Only after we answer these questions can we begin to anticipate and then build the AI-driven future we want. AI VS human doctor Although we are still in the early stages of development, artificial intelligence has the same ability to diagnose patients as doctors. Researchers at John Radcliffe Hospital in Oxford, England, have developed an AI diagnostic system that is more accurate than doctors in diagnosing heart disease for at least 80% of the time. At Harvard, researchers created a "smart" microscope that can detect potentially fatal blood infections: AI assists through training to get 25,000 slides on a series of 100,000 images to process dyes, making bacteria More obvious. The AI ​​system has been able to classify these bacteria with 95% accuracy. A study by the University of Yokohama, Japan, showed that a new computer-assisted endoscopic system can show signs of potential cancer growth in colon cancer with a sensitivity of 94%, a specificity of 79%, and an accuracy of 86%. In some cases, researchers have also found that artificial intelligence outperforms human physicians in diagnostic challenges that require rapid judgment, such as determining whether a lesion is cancerous. In a study published in the December 2017 issue of the Journal of the American Medical Association, deep learning algorithms were better able to diagnose metastatic breast cancer than time-critical human radiologists. Although human radiologists may perform well without time to review cases, in the real world, rapid diagnosis may affect the patient's life and death. Of course, IBM Watson has such a powerful diagnostic capability: when the challenge collects meaningful insights from the genetic data of tumor cells, human experts spent about 160 hours reviewing and providing treatment recommendations based on their findings. . Watson made the same feasible advice in just ten minutes. Google recently announced an open source version of DeepVariant, the company's artificial intelligence tool for analyzing genetic data. It was the most accurate tool of its kind in last year's "FDA True and False Challenge." Artificial intelligence is also better than humans before predicting health events. In April, researchers from the University of Nottingham published a study that showed that by training a large amount of data on 378,256 patients, self-study artificial intelligence predicts that patients have higher cardiovascular events than current standards of care. 7.6%. To make this number more promising, the researchers wrote: “In about 83,000 recorded samples, this is equivalent to saving an additional 355 patients. Perhaps most notably, the “false alarm†of neural networks is also With a 1.6% reduction, this risk is overestimated and may lead to unnecessary surgery or treatment, many of which are very dangerous.
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