IBM's Watson program went to study in honey. institute
This AI program has already mastered the game “Jeopardy!”. Now she will begin to study cancer.
In the final of the quiz show Jeopardy, where the best players fought against IBM's Watson program, one of the participants, admitting his defeat, next to the question attributed: “With all my heart I welcome our new computer rulers”
Now even doctors speak in a similar way. “I would like to shake Watson’s hand,” says Mark Chris , an oncologist at Sloan Kettering Cancer Center in New York. He speaks enthusiastically about the day at the end of 2013, when Watson, who is now his student, will complete a full course of study and will be ready to help doctors at the oncology center with the correct diagnoses and the definition of suitable treatments.
For Watson, this would be a very good career growth, which, however, IBM scientists had foreseen from the very beginning. They hope that Watson, an AI program with exceptional natural language processing capabilities, will become absolutely necessary in the healthcare industry. For the first time, Watson demonstrated her abilities in the game “Jeopardy” (the analogue of “Own game”), in matters of which puns and word games are actively used. To solve each question, Watson needed to understand difficult English, understand complex formulations, and then search over 200 million pages of text.
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After passing the analog honey. The Watson Institute will be able to understand the patient’s medical history, investigate test results, conduct a search in the medical literature, and issue treatment recommendations. To make the task easier to control, Watson at this stage was limited to studying only oncological diseases. Watson is currently studying lung cancer and breast cancer, but will soon begin to develop other types of cancer.
Chris, a lung cancer specialist, is working with IBM on the first iteration. He admits that the project is just an experiment at the interface of medicine and technology, but he believes that a real tool will be created based on the results of this experiment. Chris notes that now, in many cases of oncology, it is not at all easy for doctors to determine which of the chemotherapy drugs at their disposal would be the most effective. “Sometimes everything is quite obvious: if a certain genetic change has occurred, then a drug aimed at correcting this change should be prescribed. However, now for the overwhelming number of patients there is no such straightforward connection between their physical condition and what treatment they should prescribe. Today we have a lot of different drugs that can help and choosing the right one for them can make a huge difference to a patient, ”he says.
BRAIN WATSON: IBM Research Center servers in Yorktown Heights, New York, dedicated to the Watson project. Photo: IBM
Doctors are in difficulty, but Watson appears on the scene. He can go through thousands of similar cases of oncology, compare the results of treatment, review the latest achievements, the details of which are scattered over hundreds of medical journals, and then issue his recommendations on treatment. Chris explains that the goal in this case is to reproduce the decision-making process that the oncologist from Sloan-Kettering carries out. “Suppose there is an oncologist in a small town, and suddenly he gets access to all medical journals and can take advantage of the knowledge and experience of the best Sloan-Kettering specialists,” says Chris. He emphasizes that Watson will never replace a human doctor, but she can give advice and she has her first-class advisory voice. “This is a great tool for doctors, and patients will be more relaxed with it,” he says.
In the battle with the participants of the game show, Watson has settled between the two most successful players “Jeopardy!” In the entire existence of the game. On her animated avatar, the IBM logo “Smarter Planet” was depicted, the rays of light of which often shone green, indicating that Watson is on the way to victory.
The program easily managed to understand the most difficult issues. So, for example, to a question on the topic “Search for literary characters”, which sounded like “A criminal convicted for 12-year-old eating of King Hordgar's warrior is wanted. The case was entrusted to Officer Beowulf. ”Watson, with her mechanical computer voice, answered correctly:“ Grandel ”. At the bottom of the screen, viewers were shown the top three search results for answering a question, along with the degree of program confidence in each of the answers. When Watson called the monster from the epic Anglo-Saxon poem "Beowulf", which devoured the king's people, she had 97 percent confidence in the correctness of the answer.
The IBM Research group knew that Watson could not win “Jeopardy!” Only through a comprehensive database. The program also needed to learn how to interpret intricate prompts. Like a child, the program needed to learn to understand. But IBM did not have time to explain everything to the computer program, so they had to use sophisticated machine learning methods in order for Watson to quickly gain speed. Tens of thousands of question-answer pairs from past “Jeopardy!” Games were introduced into the program, so that Watson could form its own rules for displaying correct answers. The program was then tested with new questions. In the case when the answer was correct, Watson noted which algorithms from the ones at her disposal managed to build the correct search chain and lead to the correct answer.
Martin Kohn , chief medical consultant for the medical systems development group at IBM Research, said that Sloan-Kettering will have a similar process. “The program will be given information on various cases of the disease and principles of treatment, and it will have to issue its recommendations,” he says. As in the game “Jeopardy!” Watson will have to give out a ranked list of possible solutions and display the degree of their confidence in each of them. “Then one of the oncologists will say 'Yes, the Watson proposal sounds reasonable,' or vice versa, 'The Watson proposal is a complete nonsense,” says Cohn. In this way, Watson will be trained and the degree of confidence in her answers will be established.
According to Ari Caroline , director of strategic initiatives and quantitative analysis at Sloan-Kettering, who oversees the Watson machine learning process at the Oncology Center, the Sloan-Kettering team is currently introducing into Watson examples of clinical cases with all the necessary information to develop a plan treatment. At the next stage, Watson will receive examples of such cases of disease in which there is not enough information, and Watson will need to point out what it lacks.
CHAMPION: Watson utterly defeated his human opponents in two games “Jeopardy!” That aired in February 2011. Photo: Seth Wenig / Associated Press
“Oddly enough, Watson can request information from the user,” says Caroline. “Watson can say: 'I can give an answer right now, but I will be confident in it only by 30 percent, which is not very good. In order to get an answer in which I will be sure to give me more, please, information about molecular pathology, which is related to the results of these specific tests'
During the triumphant performance of Watson on the quiz show “Jeopardy!”, David Ferucci , IBM’s lead researcher on this project, spoke about the motives that prompted the company to invest so much in Watson’s development. “The desire to solve this problem is simply irresistible,” says Ferrucci, “because when we strive to solve the problem of understanding a natural language, then, in fact, we want to get into the very essence of what we consider human intelligence.”
Natural language processing can be the starting point for a wide range of different applications. IBM is already considering other areas of application for Watson, for example, its application in the field of financial analysis. However, the specialization required by the “doctor” Watson says that IBM aims to make Watson not a general practitioner, or even an all-knowing oncologist, but rather an expert on certain types of cancer. It seems that every area of activity that Watson is engaged in brings with it its specialized language and raises new questions.
No one knows this better than Caroline, who deals with all the subtleties of learning Watson medicine. “This is absolutely not like plug and play auto-connecting,” he says. “There is no such ready-made tool for processing natural language that could be easily connected, and he would immediately begin to interpret anything.”
But, despite its specialization, Watson still represents a big step towards creating universal artificial intelligence, comparable to IBM’s earlier incursion into the development of unsurpassed artificial intelligence gaming systems. The Deep Blue system developed by IBM, which won in 1997 the then world chess champion Garry Kasparov, couldn’t do anything except play chess, even couldn’t play checkers.
We still have to find out if Watson can count on repeating his success, adding to himself new knowledge in new practical areas. The project demonstrated the attractive potential of machines that can communicate with us in the same language, but at the same time it serves as a reminder that it is still too early for us to admit defeat from our computers.
Initially, this article was published in the print version of the IEEE Spectrum magazine, entitled Watson Goes to Med School.
PS In this translation, Watson is feminine, firstly because it is referred to as a program (even though it is a supercomputer too), and secondly because, as you know, Watson was a woman ;-)
In the final of the quiz show Jeopardy, where the best players fought against IBM's Watson program, one of the participants, admitting his defeat, next to the question attributed: “With all my heart I welcome our new computer rulers”Now even doctors speak in a similar way. “I would like to shake Watson’s hand,” says Mark Chris , an oncologist at Sloan Kettering Cancer Center in New York. He speaks enthusiastically about the day at the end of 2013, when Watson, who is now his student, will complete a full course of study and will be ready to help doctors at the oncology center with the correct diagnoses and the definition of suitable treatments.
For Watson, this would be a very good career growth, which, however, IBM scientists had foreseen from the very beginning. They hope that Watson, an AI program with exceptional natural language processing capabilities, will become absolutely necessary in the healthcare industry. For the first time, Watson demonstrated her abilities in the game “Jeopardy” (the analogue of “Own game”), in matters of which puns and word games are actively used. To solve each question, Watson needed to understand difficult English, understand complex formulations, and then search over 200 million pages of text.
')
After passing the analog honey. The Watson Institute will be able to understand the patient’s medical history, investigate test results, conduct a search in the medical literature, and issue treatment recommendations. To make the task easier to control, Watson at this stage was limited to studying only oncological diseases. Watson is currently studying lung cancer and breast cancer, but will soon begin to develop other types of cancer.
Chris, a lung cancer specialist, is working with IBM on the first iteration. He admits that the project is just an experiment at the interface of medicine and technology, but he believes that a real tool will be created based on the results of this experiment. Chris notes that now, in many cases of oncology, it is not at all easy for doctors to determine which of the chemotherapy drugs at their disposal would be the most effective. “Sometimes everything is quite obvious: if a certain genetic change has occurred, then a drug aimed at correcting this change should be prescribed. However, now for the overwhelming number of patients there is no such straightforward connection between their physical condition and what treatment they should prescribe. Today we have a lot of different drugs that can help and choosing the right one for them can make a huge difference to a patient, ”he says.
BRAIN WATSON: IBM Research Center servers in Yorktown Heights, New York, dedicated to the Watson project. Photo: IBM
Doctors are in difficulty, but Watson appears on the scene. He can go through thousands of similar cases of oncology, compare the results of treatment, review the latest achievements, the details of which are scattered over hundreds of medical journals, and then issue his recommendations on treatment. Chris explains that the goal in this case is to reproduce the decision-making process that the oncologist from Sloan-Kettering carries out. “Suppose there is an oncologist in a small town, and suddenly he gets access to all medical journals and can take advantage of the knowledge and experience of the best Sloan-Kettering specialists,” says Chris. He emphasizes that Watson will never replace a human doctor, but she can give advice and she has her first-class advisory voice. “This is a great tool for doctors, and patients will be more relaxed with it,” he says.
In the battle with the participants of the game show, Watson has settled between the two most successful players “Jeopardy!” In the entire existence of the game. On her animated avatar, the IBM logo “Smarter Planet” was depicted, the rays of light of which often shone green, indicating that Watson is on the way to victory.
The program easily managed to understand the most difficult issues. So, for example, to a question on the topic “Search for literary characters”, which sounded like “A criminal convicted for 12-year-old eating of King Hordgar's warrior is wanted. The case was entrusted to Officer Beowulf. ”Watson, with her mechanical computer voice, answered correctly:“ Grandel ”. At the bottom of the screen, viewers were shown the top three search results for answering a question, along with the degree of program confidence in each of the answers. When Watson called the monster from the epic Anglo-Saxon poem "Beowulf", which devoured the king's people, she had 97 percent confidence in the correctness of the answer.
The IBM Research group knew that Watson could not win “Jeopardy!” Only through a comprehensive database. The program also needed to learn how to interpret intricate prompts. Like a child, the program needed to learn to understand. But IBM did not have time to explain everything to the computer program, so they had to use sophisticated machine learning methods in order for Watson to quickly gain speed. Tens of thousands of question-answer pairs from past “Jeopardy!” Games were introduced into the program, so that Watson could form its own rules for displaying correct answers. The program was then tested with new questions. In the case when the answer was correct, Watson noted which algorithms from the ones at her disposal managed to build the correct search chain and lead to the correct answer.
Martin Kohn , chief medical consultant for the medical systems development group at IBM Research, said that Sloan-Kettering will have a similar process. “The program will be given information on various cases of the disease and principles of treatment, and it will have to issue its recommendations,” he says. As in the game “Jeopardy!” Watson will have to give out a ranked list of possible solutions and display the degree of their confidence in each of them. “Then one of the oncologists will say 'Yes, the Watson proposal sounds reasonable,' or vice versa, 'The Watson proposal is a complete nonsense,” says Cohn. In this way, Watson will be trained and the degree of confidence in her answers will be established.
According to Ari Caroline , director of strategic initiatives and quantitative analysis at Sloan-Kettering, who oversees the Watson machine learning process at the Oncology Center, the Sloan-Kettering team is currently introducing into Watson examples of clinical cases with all the necessary information to develop a plan treatment. At the next stage, Watson will receive examples of such cases of disease in which there is not enough information, and Watson will need to point out what it lacks.
CHAMPION: Watson utterly defeated his human opponents in two games “Jeopardy!” That aired in February 2011. Photo: Seth Wenig / Associated Press
“Oddly enough, Watson can request information from the user,” says Caroline. “Watson can say: 'I can give an answer right now, but I will be confident in it only by 30 percent, which is not very good. In order to get an answer in which I will be sure to give me more, please, information about molecular pathology, which is related to the results of these specific tests'
During the triumphant performance of Watson on the quiz show “Jeopardy!”, David Ferucci , IBM’s lead researcher on this project, spoke about the motives that prompted the company to invest so much in Watson’s development. “The desire to solve this problem is simply irresistible,” says Ferrucci, “because when we strive to solve the problem of understanding a natural language, then, in fact, we want to get into the very essence of what we consider human intelligence.”
Natural language processing can be the starting point for a wide range of different applications. IBM is already considering other areas of application for Watson, for example, its application in the field of financial analysis. However, the specialization required by the “doctor” Watson says that IBM aims to make Watson not a general practitioner, or even an all-knowing oncologist, but rather an expert on certain types of cancer. It seems that every area of activity that Watson is engaged in brings with it its specialized language and raises new questions.
No one knows this better than Caroline, who deals with all the subtleties of learning Watson medicine. “This is absolutely not like plug and play auto-connecting,” he says. “There is no such ready-made tool for processing natural language that could be easily connected, and he would immediately begin to interpret anything.”
But, despite its specialization, Watson still represents a big step towards creating universal artificial intelligence, comparable to IBM’s earlier incursion into the development of unsurpassed artificial intelligence gaming systems. The Deep Blue system developed by IBM, which won in 1997 the then world chess champion Garry Kasparov, couldn’t do anything except play chess, even couldn’t play checkers.
We still have to find out if Watson can count on repeating his success, adding to himself new knowledge in new practical areas. The project demonstrated the attractive potential of machines that can communicate with us in the same language, but at the same time it serves as a reminder that it is still too early for us to admit defeat from our computers.
Initially, this article was published in the print version of the IEEE Spectrum magazine, entitled Watson Goes to Med School.
PS In this translation, Watson is feminine, firstly because it is referred to as a program (even though it is a supercomputer too), and secondly because, as you know, Watson was a woman ;-)
Source: https://habr.com/ru/post/166467/
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