Abstract: The medical information processing system, which includes a server cluster configured using a plurality of virtual machines, includes a first controller that distributes a processing request to a non-emergency system processing request queue or an emergency system processing request queue depending on a type of the received processing request, a non-emergency system processing module that performs a process corresponding to a non-emergency system processing request stacked in the non-emergency system processing request queue, an emergency system processing module that performs a process corresponding to an emergency system processing request stacked in the emergency system processing request queue, and a second controller that controls the number of the processing modules, in which control by the second controller includes temporarily stopping a part of a plurality of non-emergency system processing modules in operation and newly activating the emergency system processing module.

Abstract: A system, a method, an apparatus, and a medium that are related to a medial image processing or an information processing. An image processing server that performs a plurality of types of image processing receives and a processing request from an information processing apparatus, executes image processing corresponding to the processing request, and returns a processing result to a request source. The information processing apparatus collects an operating log, calculates priority of each of the plurality of types of image processing based on the collected operating log, and updates and manages priority information. The information processing apparatus acquires a new image, determines executable image processing for the acquired image, and transmits, based on the priority of each executable image processing and on a load situation of the image processing server, a processing request to the image processing server in accordance with a criterion of the priority.

Abstract: Each of a first server installed inside a medical institution and a second server installed on a network outside the medical institution includes a server program that receives a processing request for a medical image and that outputs a processing result by executing image processing corresponding to the processing request. An image processing distributor calculates a processing waiting time required until the processing result is obtained in a case where each server executes the image processing on the medical image, based on a required time required for executing the image processing on the medical image, a network connecting situation, and the number of processing requests in a processing waiting state inside each server, and transmits the processing request for the medical image to a server having a shorter processing waiting time.

Abstract: The disclosure provides a substrate processing apparatus that processes a surface of a substrate with a processing fluid in a supercritical state, in which the substrate is protected from the pressure fluctuation caused by partial vaporization of the processing fluid in the flow path. A substrate processing apparatus which processes a surface of a substrate with a processing fluid in a supercritical state includes a chamber housing provided therein with a processing space capable of housing the substrate and a flow path which receives the processing fluid from outside and guides the processing fluid to the processing space, and a fluid supply part which pressure-feeds the processing fluid to the flow path, wherein a plurality of bent parts which change a flow direction of the processing fluid are provided in the flow path.

Abstract: This invention relates to a substrate processing technique for performing a pressure increasing step, a pressure keeping step and a pressure reducing step in this order in a processing container. A flow rate of a processing fluid in a processing space is suppressed to a second flow rate lower than a first flow rate while maintaining the processing space at a first pressure between the pressure increasing step and the pressure keeping step or in an initial stage of the pressure keeping step. In this way, the mutual diffusion between the processing fluid and a liquid in the processing space is promoted. After this diffusion proceeds, the substrate is dried by the discharge of the processing fluid from the processing space.

Abstract: A substrate processing apparatus processes a surface of a substrate with a processing fluid and includes a support tray in which a concave part for housing the substrate is provided on an upper surface thereof; a storage container in which a cavity is formed, wherein the support tray may be stored in a horizontal posture in the cavity; and a fluid supply part supplying the processing fluid to the cavity, wherein the storage container has a flow path which receives the processing fluid and discharges the processing fluid in a horizontal direction into the cavity from a discharge port that opens on a side wall surface of the cavity and toward the cavity, and a lower end position of the discharge port in a vertical direction is the same as or higher than a position of the upper surface of the support tray stored in the cavity.

Abstract: Provided are a machine learning system and method, an integration server, an information processing apparatus, a program, and an inference model creation method capable of suppressing a variation in learning data in federated learning and suppressing a variation in an inference accuracy of a model. The integration server receives an input that designates a data search condition and transmits the designated search condition to a plurality of client terminals. Each client terminal performs searching within a medical institution system to which each terminal belongs and transmits a totalization result of the number of pieces of data that matches the search condition to the integration server. The integration server receives an input that designates the required number of pieces of learning data and distributes the number of pieces of learning data used for learning on each client terminal based on the designated required number and on the received totalization result.

Abstract: Provided are a machine learning system and method, an integration server, an information processing apparatus, a program, and an inference model creation method capable of solving a problem caused by non-uniform quality of learning data in federated learning and improving an inference accuracy of a model. Each of a plurality of client terminals classifies data stored in a medical institution based on a data acquisition condition and classifies learning data into each data group acquired under the same or a similar acquisition condition. Each client terminal executes machine learning of a learning model for each learning data group classified into each condition category and transmits each learning result and condition information to an integration server. The integration server integrates received learning results for each condition category to create a plurality of master model candidates and evaluates the inference accuracy of each master model candidate.

Abstract: There are provided a machine learning system and method, an integration server, an information processing apparatus, a non-transitory computer readable medium storing a program, and an inference model creation method capable of ensuring a learning accuracy in federated learning. Each client terminal executes machine learning of the learning model using data stored in a medical institution, and transmits a learning result to the integration server. The integration server divides the plurality of client terminals into a plurality of client clusters, and creates master model candidates by integrating the learning results for each client cluster. The integration server evaluates an inference accuracy of each master model candidate, and in a case where a master model candidate having an inference accuracy lower than an accuracy threshold value is detected, extracts a client terminal as an accuracy deterioration cause from the client cluster used for creation of the master model candidate.

Abstract: There are provided a machine learning system and method, an integration server, an information processing apparatus, a non-transitory computer readable medium storing a program, and an inference model creation method capable of improving an inference accuracy of a model at an early stage in federated learning. The integration server includes a client combination optimization processing unit that performs at least one piece of processing among processing of searching a combination of the client terminals in which an inference accuracy of a master model candidate satisfies a target accuracy, the master model candidate being created by integrating the learning results of a combination of the client terminals that are some of the plurality of client terminals, and processing of searching a combination of the client terminals in which the inference accuracy of the master model candidate is maximized.

Abstract: The disclosure provides a substrate processing apparatus that processes a surface of a substrate with a processing fluid in a supercritical state, in which the substrate is protected from the pressure fluctuation caused by partial vaporization of the processing fluid in the flow path. A substrate processing apparatus which processes a surface of a substrate with a processing fluid in a supercritical state includes a chamber housing provided therein with a processing space capable of housing the substrate and a flow path which receives the processing fluid from outside and guides the processing fluid to the processing space, and a fluid supply part which pressure-feeds the processing fluid to the flow path, wherein a plurality of bent parts which change a flow direction of the processing fluid are provided in the flow path.

Abstract: A substrate processing apparatus processes a surface of a substrate with a processing fluid and includes a support tray in which a concave part for housing the substrate is provided on an upper surface thereof; a storage container in which a cavity is formed, wherein the support tray may be stored in a horizontal posture in the cavity; and a fluid supply part supplying the processing fluid to the cavity, wherein the storage container has a flow path which receives the processing fluid and discharges the processing fluid in a horizontal direction into the cavity from a discharge port that opens on a side wall surface of the cavity and toward the cavity, and a lower end position of the discharge port in a vertical direction is the same as or higher than a position of the upper surface of the support tray stored in the cavity.