Abstract: A medical image learning method includes: pre-task learning in which a model performs self-supervised learning, based on first medical image data; and target-task learning in which the model that has learned in the pre-task learning learns to detect a lesion, based on second medical image data that has a correct answer. The first medical image data includes original image data on which predetermined image processing is not performed and/or processed image data on which the predetermined image processing has been performed. The second medical image data includes the original image data.

Abstract: An analysis device includes a hardware processor, an acquirer, and an outputter, wherein the hardware processor acquires first medically-related information obtained through computer processing performed on medical information, the hardware processor generates structured data by structuring unstructured data acquired from user-created information on the basis of the medical information, the acquirer acquires second medically-related information from the structured data, the hardware processor compares the acquired first medically-related information and the second medically-related information acquired by the acquirer, and the outputter outputs next step information on the basis of a comparison result from the comparing.

Abstract: A learning apparatus includes a hardware processor. The hardware processor obtains a first medical image. The hardware processor generates a second medical image in which a feature according to feature information related to a portion other than a recognition target of the first medical image is made close to the feature according to standard feature information which is to be a predetermined standard. The second medical image is used to train a machine learning model.

Abstract: Provided is an information processing device that is interposed between an imaging control device and an image management device in communication. The information processing device including an abnormality detector and a first hardware processor. The abnormality detector performs detection of an abnormality in a medical image received from the imaging control device. The first hardware processor that determines, based on a result of the detection by the abnormality detector, content or a destination of transmission of the medical image or the result of the detection.

Abstract: Provided is a medical image analysis system including: an acquirer that acquires a medical image obtained by imaging of a patient to be diagnosed; an estimator that estimates an index value indicating a respiratory function from the acquired medical image; and a hardware processor that causes an output unit to output the estimated index value.