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AI가 일상의 많은 영역으로 파고들고, 스마트폰 어플리케이션이 운동량이나 수면의 질 등 건강 관리를 하고 있습니다. 그렇다면 전문병원에서는 어떤 변화가 일어나고 있을까요? 암 진단을 돕는 AI 의사 왓슨은 대학병원에만 있는 것이 아닙니다. 진료와 연구에 있어 첨단을 달리는 전문병원들도 AI를 개발하고 진료 과정에 도입하고 있습니다. 본 도서는 AI를 직접 개발한 시력교정 전문병원의 AI 개발 이유와 과정, AI 도입으로 달라진 점을 고찰하고 AI 도입을 통해 의료계에서 고객가치와 서비스가 어떻게 달라지고 있는 지를 살펴봅니다. 헬스케어 산업의 최신 경향을 파악할 수 있으며, AI와 사람의 일이 어떻게 조화를 이룰 수 있는지도 전망해볼 수 있습니다.
목차
Intro: Beyond vision correction
Chapter 1 AI made by an ophthalmologist
AI in front of my eyes
Chapter 2 The present of medical AI
Perspective of medical AI
AI is not the master key
Chapter 3 Why did B&VIIT develop AI?
Is Doctor shopping bad?
Of the doctor, for the doctor and by the doctor
B&VIIT AI Q&A
Chapter 4 Diverse Vision Correction Methods
Vision correction is ablation of cornea
Chapter 5 B&VIIT AI
Can I receive refractive surgery?
Find the optimal visual correction: B&VIIT AI 1
Predict vision after surgery: B&VIIT AI 2
Find the optimal refraction value: B&VIIT AI 3
Chapter 6 Doctors researching AI
Research direction of AI vision correction
The reason why doctors develop AI
What will doctors do in the era of AI?
Chapter 7 Data, data, data
Deciding the success or failure of AI
Data of the B&VIIT Eye Center
Development of Medical AI
Chapter 8 Possibility and value of medical AI
Possibility of vision correction AI
Seeing systemic disease with the eye
Dreaming of an even medical treatment
Is the spring of AI over?
Problems after introduction of medical AI
Chapter 9 Future of visual correction hospitals
The Future to come
Writers
About B&VIIT
Chapter 1 AI made by an ophthalmologist
AI in front of my eyes
Chapter 2 The present of medical AI
Perspective of medical AI
AI is not the master key
Chapter 3 Why did B&VIIT develop AI?
Is Doctor shopping bad?
Of the doctor, for the doctor and by the doctor
B&VIIT AI Q&A
Chapter 4 Diverse Vision Correction Methods
Vision correction is ablation of cornea
Chapter 5 B&VIIT AI
Can I receive refractive surgery?
Find the optimal visual correction: B&VIIT AI 1
Predict vision after surgery: B&VIIT AI 2
Find the optimal refraction value: B&VIIT AI 3
Chapter 6 Doctors researching AI
Research direction of AI vision correction
The reason why doctors develop AI
What will doctors do in the era of AI?
Chapter 7 Data, data, data
Deciding the success or failure of AI
Data of the B&VIIT Eye Center
Development of Medical AI
Chapter 8 Possibility and value of medical AI
Possibility of vision correction AI
Seeing systemic disease with the eye
Dreaming of an even medical treatment
Is the spring of AI over?
Problems after introduction of medical AI
Chapter 9 Future of visual correction hospitals
The Future to come
Writers
About B&VIIT
책속으로
An ophthalmologist made AI?
What can an ophthalmologist do with AI?Over eight million smart speakers were sold by the end of 2019.
Yes, we too use AI-based smart speakers. We call the speaker as soon as we wake up in the morning. However, do we have to use the AI to do this? We can do this easily by a few movements of the fingers on a smartphone.
These are all different forms of AI too. Regardless of whether you ask or not, the AI does the task for you. It is amazing and convenient that they do it for you, even though you did not know you needed it and did not ask for it.
Then, can it respond to things you did not ask? There are things we must always ask and respond ourselves. For example, the patients’ vision after a SMILE surgery, lens size befitting the patient for the ICL implantation, and the optical power of the intraocular lens during cataract surgery.
Not only doctors, but also counselors must ask themselves endlessly by looking at the accumulating checkup results while the patients are in the process of being checked up. - Is refractive surgery possible for this person?
- Then what surgical option is appropriate?
- What will the vision be after surgery?Is it possible for AI to respond to such questions? Then, we can consider the patients’ perspective and interact with them more deeply and warmly.
Why doctors talk about figures
Doctors typically talk about figures (in other words, numerical digits), not because they like it, but because figures are an important part of the treatment and visual correction. Here is an example.
“This patient has a thick cornea, and the right and left myopia is -6.50 diopter and the with-the-rule astigmatism* is 2.00 diopter; therefore, if the figures are entered in the surgery nomogram as such and a femtosecond laser is used to a particular degree, the myopia should disappear after surgery, following which the predicted visual acuity would be 1.2 in the decimal scale. Since the xerophthalmia is low and pupil size is relatively small, the associated inconvenience after surgery is not expected to be big.”
*The myopia that leads to blurry vision, due to the lack of correct focus, can be classified broadly into with-the-rule astigmatism and against-the-rule astigmatism depending on the location of the focal line with the strongest refraction.
When consulting the patient to receive visual correction through SMILE surgery, it is crucial that the doctor promptly checks the preoperative measurement results with the eye, examines the patient’s eyes with slit lamp microscope, and calculates the surgical values. To ensure a precise and safe surgery, the calculations need to be repeatedly verified. Since the doctor must concentrate on precisely calculating each figure in the presence of the patient; furthermore, the doctor has no reserve power to listen to all the patients’ stories. However, if the AI would be tasked with the calculations, the doctor would be able to focus on the patient’s eyes, rather than at the monitor. It is almost as if the eyes of the patient were looking at my eyes to meet a bright world.
Since a precise calculation that was performed by a machine would be better than those performed by humans, the several calculations required for visual correction surgery can also be better performed by AI. This is considering if AI is taught with our knowledge and experience.
Recently, rather than AI, which primarily replaces the human intelligence, augmented intelligence was conceptualized. This aims to supplement human intelligence rather than replace it. Therefore, the latter AI will be of substantial aid to solving our problems.
Why ophthalmologists see the image?
An important ophthalmological characteristic makes us consider AI. Unlike other treatment subjects that show the diagnosis results with a few figures, most ophthalmological evaluation involves complex figures and images. Deciphering the evaluation results is similar to diagnostic radiology. However, unlike black and white x-ray, MRI and CT, the ophthalmological evaluation also includes several 3D and colored images. Therefore, ophthalmology is an area where AI is most actively being researched. Analyzing just one eye constitutes data of approximately 70 images; however, in most situations both eyes require investigation and analysis. Therefore, we believe this sufficiently explains the amount of image data that is produced for an ophthalmologist to review before treatment and for planning the surgery. Considering these characteristics of ophthalmology, many prominent global firms such as Google are focusing on developing ophthalmological AI to judge the systematic health state, as well as the retina, through fundus photography (1).
Generally, the Pentacam is the representative checkup of an ophthalmologist. It can precisely check the state of the cornea before surgery and is a checkup tool that can diagnose conical cornea, which is a condition that should not receive visual correction surgery. This checkup is deciphered through 3D and high-quality color images and figures of the frontal region of the eyes such as the cornea and the anterior chamber. Slit lamp and corneal topography images of a normal cornea This checkup result, which looks like a sandglass, indicates a normal corneal shape, which is appropriate for surgery. Slit lamp and corneal topography images of an abnormal cornea In contrast, in a case as that shown above with an irregular or horse’s hoof shaped cornea, general laser visual correction surgery is preferably avoided, but customized laser surgery must be considered.
An experienced visual correction ophthalmologist can intuitively decide by seeing such color images, shapes, and figures, whether it is a normal eye or an eye that can undergo visual correction surgery. Greater amount of experience is associated with a deeper judgment and understanding of treatment modality and checkup outcome. Therefore, a higher level of experience has been correlated with a more precise treatment and surgery planning.
However, judging and interpreting complex figures and images from preoperative examinations is precisely what AI can also perform with a considerable degree of accuracy. If a large amount of data is used to train the models, the machine learning based AI can provide an output in one attempt and categorize into a normal eye where general laser ablation surgery is possible, or an eye that requires a customized surgical approach or an eye that should not receive surgery.
A schematic illustrating the logical process to identify the candidates for corneal refractive surgery.
What ophthalmologists do with AI?If the AI that has learnt the demographic information of the patient receiving surgery and clinical decision-making database of the doctor were to acquire the checkup results of the new patient, it can help the doctor by assisting the system. Specifically, what one can expect from the AI is the precision of judgment that is expected of highly skilled doctors and counselors. This indicates that an additional trustworthy basis of judgment has been made for doctors and patients.
Then, is this good for the doctors? Or is it good for the patients? It is good for patients because they can be recommended, the precise surgical methods that are safe and personalized. It is also good for doctors that are lacking in knowledge and experience as it eliminates the proficiency gap.
Therefore, does it mean that it is not particularly needed for experienced doctors? Although it may not be necessary, it could act as an added advantage. Considering the fact that doctors too, are humans, and they can make human errors, due to either their emotions or fatigue. Here, AI can support doctors as a very objective revalidation system.
That is why we decided to design an AI. We have designed it based on a large quanta of data of 420,000 eyes and will continue to
What can an ophthalmologist do with AI?Over eight million smart speakers were sold by the end of 2019.
Yes, we too use AI-based smart speakers. We call the speaker as soon as we wake up in the morning. However, do we have to use the AI to do this? We can do this easily by a few movements of the fingers on a smartphone.
These are all different forms of AI too. Regardless of whether you ask or not, the AI does the task for you. It is amazing and convenient that they do it for you, even though you did not know you needed it and did not ask for it.
Then, can it respond to things you did not ask? There are things we must always ask and respond ourselves. For example, the patients’ vision after a SMILE surgery, lens size befitting the patient for the ICL implantation, and the optical power of the intraocular lens during cataract surgery.
Not only doctors, but also counselors must ask themselves endlessly by looking at the accumulating checkup results while the patients are in the process of being checked up. - Is refractive surgery possible for this person?
- Then what surgical option is appropriate?
- What will the vision be after surgery?Is it possible for AI to respond to such questions? Then, we can consider the patients’ perspective and interact with them more deeply and warmly.
Why doctors talk about figures
Doctors typically talk about figures (in other words, numerical digits), not because they like it, but because figures are an important part of the treatment and visual correction. Here is an example.
“This patient has a thick cornea, and the right and left myopia is -6.50 diopter and the with-the-rule astigmatism* is 2.00 diopter; therefore, if the figures are entered in the surgery nomogram as such and a femtosecond laser is used to a particular degree, the myopia should disappear after surgery, following which the predicted visual acuity would be 1.2 in the decimal scale. Since the xerophthalmia is low and pupil size is relatively small, the associated inconvenience after surgery is not expected to be big.”
*The myopia that leads to blurry vision, due to the lack of correct focus, can be classified broadly into with-the-rule astigmatism and against-the-rule astigmatism depending on the location of the focal line with the strongest refraction.
When consulting the patient to receive visual correction through SMILE surgery, it is crucial that the doctor promptly checks the preoperative measurement results with the eye, examines the patient’s eyes with slit lamp microscope, and calculates the surgical values. To ensure a precise and safe surgery, the calculations need to be repeatedly verified. Since the doctor must concentrate on precisely calculating each figure in the presence of the patient; furthermore, the doctor has no reserve power to listen to all the patients’ stories. However, if the AI would be tasked with the calculations, the doctor would be able to focus on the patient’s eyes, rather than at the monitor. It is almost as if the eyes of the patient were looking at my eyes to meet a bright world.
Since a precise calculation that was performed by a machine would be better than those performed by humans, the several calculations required for visual correction surgery can also be better performed by AI. This is considering if AI is taught with our knowledge and experience.
Recently, rather than AI, which primarily replaces the human intelligence, augmented intelligence was conceptualized. This aims to supplement human intelligence rather than replace it. Therefore, the latter AI will be of substantial aid to solving our problems.
Why ophthalmologists see the image?
An important ophthalmological characteristic makes us consider AI. Unlike other treatment subjects that show the diagnosis results with a few figures, most ophthalmological evaluation involves complex figures and images. Deciphering the evaluation results is similar to diagnostic radiology. However, unlike black and white x-ray, MRI and CT, the ophthalmological evaluation also includes several 3D and colored images. Therefore, ophthalmology is an area where AI is most actively being researched. Analyzing just one eye constitutes data of approximately 70 images; however, in most situations both eyes require investigation and analysis. Therefore, we believe this sufficiently explains the amount of image data that is produced for an ophthalmologist to review before treatment and for planning the surgery. Considering these characteristics of ophthalmology, many prominent global firms such as Google are focusing on developing ophthalmological AI to judge the systematic health state, as well as the retina, through fundus photography (1).
Generally, the Pentacam is the representative checkup of an ophthalmologist. It can precisely check the state of the cornea before surgery and is a checkup tool that can diagnose conical cornea, which is a condition that should not receive visual correction surgery. This checkup is deciphered through 3D and high-quality color images and figures of the frontal region of the eyes such as the cornea and the anterior chamber. Slit lamp and corneal topography images of a normal cornea This checkup result, which looks like a sandglass, indicates a normal corneal shape, which is appropriate for surgery. Slit lamp and corneal topography images of an abnormal cornea In contrast, in a case as that shown above with an irregular or horse’s hoof shaped cornea, general laser visual correction surgery is preferably avoided, but customized laser surgery must be considered.
An experienced visual correction ophthalmologist can intuitively decide by seeing such color images, shapes, and figures, whether it is a normal eye or an eye that can undergo visual correction surgery. Greater amount of experience is associated with a deeper judgment and understanding of treatment modality and checkup outcome. Therefore, a higher level of experience has been correlated with a more precise treatment and surgery planning.
However, judging and interpreting complex figures and images from preoperative examinations is precisely what AI can also perform with a considerable degree of accuracy. If a large amount of data is used to train the models, the machine learning based AI can provide an output in one attempt and categorize into a normal eye where general laser ablation surgery is possible, or an eye that requires a customized surgical approach or an eye that should not receive surgery.
A schematic illustrating the logical process to identify the candidates for corneal refractive surgery.
What ophthalmologists do with AI?If the AI that has learnt the demographic information of the patient receiving surgery and clinical decision-making database of the doctor were to acquire the checkup results of the new patient, it can help the doctor by assisting the system. Specifically, what one can expect from the AI is the precision of judgment that is expected of highly skilled doctors and counselors. This indicates that an additional trustworthy basis of judgment has been made for doctors and patients.
Then, is this good for the doctors? Or is it good for the patients? It is good for patients because they can be recommended, the precise surgical methods that are safe and personalized. It is also good for doctors that are lacking in knowledge and experience as it eliminates the proficiency gap.
Therefore, does it mean that it is not particularly needed for experienced doctors? Although it may not be necessary, it could act as an added advantage. Considering the fact that doctors too, are humans, and they can make human errors, due to either their emotions or fatigue. Here, AI can support doctors as a very objective revalidation system.
That is why we decided to design an AI. We have designed it based on a large quanta of data of 420,000 eyes and will continue to
출판사 서평
This book examines the reasons and process of AI development at the Vision Correction Hospital, which developed AI, and the changes that resulted from the introduction of AI. You can see the latest trends in the healthcare industry and see how AI and human work can work together. In order to see how artificial intelligence is changing customer value and service in the medical field, it contains various discussions about medical AI. We have looked at the current issues that need to be considered, including medical insurance benefits. Advances in medical technology can be achieved only by the research, time, and experience of each other's experts, not by some outstanding research or medicine. That's why the book included 11 specialists from inside and outside the medical community, including AI startups, medical AI researchers, machine learning professionals, and services. It is a book that examines the present of medical and artificial intelligence and looks forward to the future based on the content of experts in various fields.
상품 정보 고시
| 도서명 | B&VIIT AI REPORT |
|---|---|
| 저자 | B&VIIT Eye Center |
| 출판사 | 비앤빛에이아이 |
| ISBN | 9791196885618 (1196885613) |
| 쪽수 | 208 |
| 출간일 | 2020-01-15 |
| 사이즈 | 135 * 201 * 18 mm /283g |
| 목차 또는 책소개 | Intro: Beyond vision correction Chapter 1 AI made by an ophthalmologist AI in front of my eyes Chapter 2 The present of medical AI Perspective of medical AI AI is not the master key Chapter 3 Why did B&VIIT develop AI? Is Doctor shopping bad? Of the doctor, for the doctor and by the doctor B&VIIT AI Q&A Chapter 4 Diverse Vision Correction Methods Vision correction is ablation of cornea Chapter 5 B&VIIT AI Can I receive refractive surgery? Find the optimal visual correction: B&VIIT AI 1 Predict vision after surgery: B&VIIT AI 2 Find the optimal refraction value: B&VIIT AI 3 Chapter 6 Doctors researching AI Research direction of AI vision correction The reason why doctors develop AI What will doctors do in the era of AI? Chapter 7 Data, data, data Deciding the success or failure of AI Data of the B&VIIT Eye Center Development of Medical AI Chapter 8 Possibility and value of medical AI Possibility of vision correction AI Seeing systemic disease with the eye Dreaming of an even medical treatment Is the spring of AI over? Problems after introduction of medical AI Chapter 9 Future of visual correction hospitals The Future to come Writers About B&VIIT |
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