Ophthalmology is a subject that highly depends on imaging examination.Artificial intelligence(AI)technology has great potential in medical imaging analysis,including image diagnosis,classification,grading,guiding trea...Ophthalmology is a subject that highly depends on imaging examination.Artificial intelligence(AI)technology has great potential in medical imaging analysis,including image diagnosis,classification,grading,guiding treatment and evaluating prognosis.The combination of the two can realize mass screening of grass-roots eye health,making it possible to seek medical treatment in the mode of“first treatment at the grass-roots level,two-way referral,emergency and slow treatment,and linkage between the upper and lower levels”.On the basis of summarizing the AI technology carried out by scholars and their teams all over the world in the field of ophthalmology,quite a lot of studies have confirmed that machine learning can assist in diagnosis,grading,providing optimal treatment plans and evaluating prognosis in corneal and conjunctival diseases,ametropia,lens diseases,glaucoma,iris diseases,etc.This paper systematically shows the application and progress of AI technology in common anterior segment ocular diseases,the current limitations,and prospects for the future.展开更多
AIMTo investigate the relationship between the ultrasound biomicroscopic (UBM) features of anterior-segment cysts (ASCs) and increased intraocular pressure (IOP) as a risk factor for closed-angle glaucoma (CAG).
著名生物学家爱德华·威尔逊(Edward O Wilson)在其名作《一致性:知识的统一》(Consilience:The Unity of Knowledge)中提出跨学科整合与协调的必要性。他将融合定义为“知识的‘跳跃式结合',即通过事实的相互关联……创造出一...著名生物学家爱德华·威尔逊(Edward O Wilson)在其名作《一致性:知识的统一》(Consilience:The Unity of Knowledge)中提出跨学科整合与协调的必要性。他将融合定义为“知识的‘跳跃式结合',即通过事实的相互关联……创造出一个共同的解释基础。”文章的假设是,与基础生物医学研究需要来源于最新技术的数据几乎一样,整合现有知识同样极其重要。这涉及到解决相互矛盾的发现、减少“信息孤岛”、以及承认复杂的必要性。我们以角膜和晶状体作为我们假设的案例研究。具体来说,在这种视角下,我们讨论蛋白质聚集、氧化损伤和纤维化方面相互矛盾和碎片化的信息。这些研究领域与眼前节研究紧密相关。我们的目的是强调威尔逊的知识融合统一的迫切需要,从而增强严谨性和可重复性,最重要的是,促进对知识的深入理解,而不只是知道。展开更多
基金Supported by National Natural Science Foundation of China(No.82101097,No.82070937).
文摘Ophthalmology is a subject that highly depends on imaging examination.Artificial intelligence(AI)technology has great potential in medical imaging analysis,including image diagnosis,classification,grading,guiding treatment and evaluating prognosis.The combination of the two can realize mass screening of grass-roots eye health,making it possible to seek medical treatment in the mode of“first treatment at the grass-roots level,two-way referral,emergency and slow treatment,and linkage between the upper and lower levels”.On the basis of summarizing the AI technology carried out by scholars and their teams all over the world in the field of ophthalmology,quite a lot of studies have confirmed that machine learning can assist in diagnosis,grading,providing optimal treatment plans and evaluating prognosis in corneal and conjunctival diseases,ametropia,lens diseases,glaucoma,iris diseases,etc.This paper systematically shows the application and progress of AI technology in common anterior segment ocular diseases,the current limitations,and prospects for the future.
文摘AIMTo investigate the relationship between the ultrasound biomicroscopic (UBM) features of anterior-segment cysts (ASCs) and increased intraocular pressure (IOP) as a risk factor for closed-angle glaucoma (CAG).
文摘著名生物学家爱德华·威尔逊(Edward O Wilson)在其名作《一致性:知识的统一》(Consilience:The Unity of Knowledge)中提出跨学科整合与协调的必要性。他将融合定义为“知识的‘跳跃式结合',即通过事实的相互关联……创造出一个共同的解释基础。”文章的假设是,与基础生物医学研究需要来源于最新技术的数据几乎一样,整合现有知识同样极其重要。这涉及到解决相互矛盾的发现、减少“信息孤岛”、以及承认复杂的必要性。我们以角膜和晶状体作为我们假设的案例研究。具体来说,在这种视角下,我们讨论蛋白质聚集、氧化损伤和纤维化方面相互矛盾和碎片化的信息。这些研究领域与眼前节研究紧密相关。我们的目的是强调威尔逊的知识融合统一的迫切需要,从而增强严谨性和可重复性,最重要的是,促进对知识的深入理解,而不只是知道。