An ophthalmic system comprising: a plurality of ophthalmic imaging apparatuses (2000-in) including a plurality of slit lamp microscopes; and an information processing system (5000, 5001, 5002) connected to each of the plurality of ophthalmic imaging apparatuses (2000-in) via a communication path, wherein each of the plurality of ophthalmic imaging apparatuses (2000-in) includes: an image acquisition unit configured to acquire a three dimensional image by photographing a subject's eye; and a first communication unit configured to transmit the three dimensional image to the information processing system (5000, 5001, 5002), and the information processing system (5000, 5001, 5002) includes: a second communication unit configured to receive the three dimensional image transmitted by the first communication unit; an image storage configured to store a plurality of three dimensional images received by the second communication unit; a first processor configured to acquire knowledge by performing at least one of machine learning and data mining, based on the plurality of three dimensional images; a knowledge storage configured to store knowledge acquired by the first processor; and a second processor configured to generate diagnosis support information by performing inference based on a three dimensional image of a subject's eye transmitted from one of the plurality of slit lamp microscopes and received by the second communication unit and based on the knowledge stored in the knowledge storage, wherein the second processor includes a region-of-interest identifying means configured to identify a region of interest of the three dimensional image of the subject's eye by analyzing the three dimensional image, and is configured to generate diagnosis support information including any of a suspected disease name, presence or absence of a specific disease, severity, necessity for an examination, a type of examination, necessity for a surgery, and a type of surgery by performing inference based on the identified region of interest and the knowledge stored in the knowledge storage. a plurality of ophthalmic imaging apparatuses (2000-in) including a plurality of slit lamp microscopes; and an information processing system (5000, 5001, 5002) connected to each of the plurality of ophthalmic imaging apparatuses (2000-in) via a communication path, wherein each of the plurality of ophthalmic imaging apparatuses (2000-in) includes: an image acquisition unit configured to acquire a three dimensional image by photographing a subject's eye; and a first communication unit configured to transmit the three dimensional image to the information processing system (5000, 5001, 5002), and an image acquisition unit configured to acquire a three dimensional image by photographing a subject's eye; and a first communication unit configured to transmit the three dimensional image to the information processing system (5000, 5001, 5002), and the information processing system (5000, 5001, 5002) includes: a second communication unit configured to receive the three dimensional image transmitted by the first communication unit; an image storage configured to store a plurality of three dimensional images received by the second communication unit; a first processor configured to acquire knowledge by performing at least one of machine learning and data mining, based on the plurality of three dimensional images; a knowledge storage configured to store knowledge acquired by the first processor; and a second processor configured to generate diagnosis support information by performing inference based on a three dimensional image of a subject's eye transmitted from one of the plurality of slit lamp microscopes and received by the second communication unit and based on the knowledge stored in the knowledge storage, a second communication unit configured to receive the three dimensional image transmitted by the first communication unit; an image storage configured to store a plurality of three dimensional images received by the second communication unit; a first processor configured to acquire knowledge by performing at least one of machine learning and data mining, based on the plurality of three dimensional images; a knowledge storage configured to store knowledge acquired by the first processor; and a second processor configured to generate diagnosis support information by performing inference based on a three dimensional image of a subject's eye transmitted from one of the plurality of slit lamp microscopes and received by the second communication unit and based on the knowledge stored in the knowledge storage, wherein the second processor includes a region-of-interest identifying means configured to identify a region of interest of the three dimensional image of the subject's eye by analyzing the three dimensional image, and is configured to generate diagnosis support information including any of a suspected disease name, presence or absence of a specific disease, severity, necessity for an examination, a type of examination, necessity for a surgery, and a type of surgery by performing inference based on the identified region of interest and the knowledge stored in the knowledge storage.