Abstract: Provided is an image diagnostic system that diagnoses a medical image using an artificial intelligence function. The image diagnostic system includes: a control unit; a diagnosis unit that estimates a diagnosis result using a machine learning model on the basis of an input image; a diagnosis result report output unit that outputs a diagnosis result report on the basis of the diagnosis result; a selection unit that selects a part of a diagnostic content included in the diagnostic result report; and an extraction unit that extracts determination basis information that has affected estimation of the diagnosis content selected, in which the control unit outputs the determination basis information. The image diagnostic system further includes a correction unit that corrects the determination basis information, in which the determination basis information corrected is used for relearning of the machine learning model.

Abstract: There is provided an information processing device including a storage unit that stores first annotation data generated from image data of a biological specimen and conversion processing information, a conversion unit that converts, using the conversion processing information, the first annotation data into a plurality of second annotation data incidental to the first annotation data, and an output unit that outputs the first annotation data or the second annotation data.

Abstract: In parallel with an operation of browsing a pathological-tissue image, retrieval of similar cases from past cases using image information about the pathological-tissue image is automatically performed. An analysis apparatus of the present disclosure includes a first setting unit configured to set sample regions in an analysis target region of an image obtained by imaging of a biologically-originated sample, on the basis of an algorithm; a processing unit configured to select at least one reference image from a plurality of reference images associated with a plurality of cases, on the basis of images of the sample regions; and an output unit configured to output the selected reference image.

Abstract: Making it possible to improve accuracy of machine learning. A determination support device includes: a derivation unit (100) that derives an estimation result of determination on a first pathological image obtained by imaging a biological sample, the derivation being performed using a multi-stage trained model in which class classification can be set in each stage.

Abstract: An estimation result can be more effectively utilized. An information processing apparatus includes a deriving unit (100) that derives an estimation result of diagnosis for a second pathology image using a trained model on which learning has performed using training data including a plurality of first pathology images, and an identifying unit (100) that identifies a basis image that serves as a basis for derivation of the estimation result by the trained model from the plurality of first pathology images.

Abstract: The usability in annotating an image of a subject derived from a living body is improved. An image analysis method is implemented by one or more computers and includes: displaying a first image that is an image of a subject derived from a living body; acquiring information regarding a first region based on a first annotation added to the first image by a user (S101); specifying a similar region similar to the first region from a region different from the first region in the first image, or a second image obtained by image capture of a region including at least a part of a region of the subject subjected to capture of the first image, based on the information regarding the first region (S102, S103); and displaying a second annotation in a second region corresponding to the similar region in the first image (S104).