Abstract: A system and method for pre-operative or intra-operative surgical procedure feedback provide a recommendation to a surgeon. A system may include a robotic surgical device to perform a portion of a surgical procedure on a patient, and a processor to determine a recommendation, based on past surgical information, for the portion of the surgical procedure performed by the robotic surgical device or for a next action to be taken, but the robotic surgical device or a surgeon. The system may include outputting the recommendation by intra-operatively providing the recommendation to a surgeon operating the robotic surgical device.

Abstract: A method of providing a user with an individualized health platform, includes collecting a user's health and care data, organizing the collected health and care data into a problem oriented health record, drafting health goals and a care plan for the user with the aid of a health coach, vetting the health goals and care plan using a data and analytics system to assure that the health goals and care plan are supported by peer reviewed health and clinical literature, producing individualized guidance options for addressing new acute or chronic issues, managing existing health issues, achieving the health goals, and adhering to the care plan based on the user's problem oriented health record, monitoring the user's achievements with respect to the user's health goals and adherence to the care plan, and providing additional guidance options based on the user's new health and care issues and the user's achievements and adherence.

Abstract: A medical information management apparatus has processing circuitry configured to search medical information in a storage, when accepting a search request of the medical information including a key being an item of information regarding a patient and a value being contents of the key, and extract the medical information matching a search condition as condition-matched medical information; extract the key and the value from the condition-matched medical information, calculate a matching rate being a proportion of the value included in the condition-matched medical information to the entire medical information in the storage, and determine that the value is idiosyncratic information when the matching rate is equal to or less than a threshold set with respect to the key; and determine whether the key of the value determined to include the idiosyncratic information corresponds to an essential key which is essential in terms of a purpose of utilization.

Abstract: Decision support technology is provided for use with patients who may be prone to a cardiovascular condition such as acute coronary syndromes. A mechanism is provided to determine a patient's risk for experiencing a cardiovascular ischemic event at a future time interval based on temporal patterns determined using physiological parameters of the patient such as serum or blood uric acid and/or C-reactive protein (CRP). A forecast or score may be determined indicating whether or not temporal patterns merit intervention to prevent occurrence or reoccurrence of ischemic events, or for determining adherence to or efficacy of treatment or preventive interventions. Based on the forecast or score, appropriate response action such as automatically issuing an alert or notification to a caregiver associated with the patient, may be determined, recommended, or implemented.

Abstract: Methods and systems of summarizing medical data. One system includes an electronic processor configured to analyze medical data to extract a medical concept and a plurality of additional attributes of the medical concept and store the medical concept and the plurality of additional attributes. The electronic processor is configured to generate a first medical summary associated with the patient, where the first medical summary is based on the stored medical concept and at least a first additional attribute included in the stored plurality of additional attributes. The electronic processor is configured to receive a user interaction with the first medical summary. The electronic processor is configured to generate a second medical summary associated with the patient based on the user interaction, the second medical summary is based on the stored medical concept and at least a second additional attribute included in the stored plurality of additional attributes.

Abstract: Methods, apparatuses, and systems for edge computing for robotic telesurgery using artificial intelligence are disclosed. A robotic surgical system includes surgery equipment and can communicate via a cloud network. The system can include operation room (OR) equipment and a surgical computer. The surgical computer transfers data between a remote surgeon, the OR equipment, and the surgery equipment. The surgical computer receives, using the OR equipment and the surgery equipment, data related to a surgical procedure. The data is related to the surgical procedure and is computed using artificial intelligence (AI). The surgical computer determines a risk assessment based on data related to the surgery equipment. The surgical computer sends an indication of the determined risk assessment to the remote surgeon.

Abstract: A telemedicine platform utilizes artificial intelligence to match patients with practitioners. The platform includes a virtual assistant operable to automatically generate responses to a patient using machine learning in order to further identify details regarding the patient's symptoms and needs. The virtual assistant includes a digitally generated human face that automatically adapts mouth-movements and facial expressions to match the automatically generated responses in order to provide a feeling of interacting with a human assistant. The platform includes a patient interface, for identifying physicians and scheduling appointments, a practitioner interface, for managing patients and scheduling issues, and an administrator interface, for managing a larger practice of multiple practitioners.

Abstract: An electronic record management system includes a server and a plurality of electronic record display terminals in electronic communication with the server. Each electronic record display terminal includes a monitor screen. The server stores a list of cases each with an associated case identifier, stores a list of staff members each with an associated staff identifier, and stores documents associated with each case. The server creates an electronic sticky note and a display format of the electronic sticky note. The server electronically communicates with at least one of the electronic record display terminals to cause the monitor screen of the at least one electronic record display terminal to display an electronic record of one of the cases along with the electronic sticky note overlaid over a portion of the electronic record.

Abstract: A method for continuous data transfer is provided. Data blocks are generated from a continuous data stream captured via a physiological monitoring device by segmenting data from the continuous data stream into the data blocks. A time at which the data associated with each data block occurs is determined and a sample number is associated with each data block. The data blocks are transmitted from the physiological monitoring device to a server. The data blocks are ordered on the server based on the time and the sample number associated with each data block.

Abstract: One or more devices that provides an immersive cerebral salubrity retention and selection package (ICSRSP) to potential new patients (PNPs) comprising customized cerebral salubrity care personnel with available personal time periods to improve their cerebral salubrity. An ICSRSP determines whether a PNP qualifies for a cerebral health immersion program (CHIP). The ICSRSP generates a set of interrogatives based on data and data sets (used for a determination) that are not included in initially collected data regarding the PNP. The PNP's acceptance into the ICSRSP is based on an assessment of the PNP data and PNP-provided responses to the interrogatives. If the PNP is selected for the CHIP, an option is provided to the PNP to enroll in the CHIP to become a patient. If additional information is needed to complete an acceptance process for the CHIP, a user interface is provided enabling the PNP to provide data for process completion.

Abstract: Embodiments are directed to managing the provisioning of healthcare services. A visit profile that includes a reason for the visit and patient demographic information may be provided by a patient requesting a visit to obtain healthcare services. Match scores for providers may be generated based on matching models and the visit profile. A provider may be assigned to the visit based on the match scores. A virtual waiting room may be provided for the patient based on the visit profile. The visit profile may be updated with supplemental information based on the interactions between the patient and the virtual waiting room, patient information, or visit information. Updated match scores may be provided for the providers based on the updated visit profile. If an updated match score exceeds a previously determined higher match score, another provider associated with a higher match score may be assigned to the visit.

Abstract: Systems and methods are provided for monitoring a user having a chronic gastrointestinal indication. A questionnaire regarding a plurality of conditions is provided on a repeating basis. Each such condition at least partly arises from the gastrointestinal indication. Questionnaire questions are each associated with a corresponding condition and provide an affordance that allows the user to select between low and high values in accordance with user association with the condition. Responses are stored in a data store associated with the user. A user requested report comprising a graphical quality of life measure of the user is provided based upon temporal questionnaire answers. Questionnaire information is communicated to a remote device for medical practitioner evaluation and computation of a temporal overall quality of life score based on a plurality of component quality of life scores, each of which is associated with a condition in the plurality of conditions.

Abstract: A neural network is trained with patient historical data including features of patient pathways and labels characterizing a type of the patient pathways. During a runtime phase, the trained neural network matches a current patient profile with the patient historical data to extract selected portions of clinical practice guidelines (CPGs) identified according to one or more generated CPG models, the patient pathway models, and the current patient profile.

Abstract: A computer-implemented method for clinical decision support is provided according to an embodiment of the present disclosure. In the method, patient information can be obtained that comprises at least one clinical condition. A graph can be searched for at least one rule matching the at least one clinical condition. The graph represents a plurality of rule sets. The rule set comprises one or more rule. The rule can be indicated with a path comprising at least one first node and a second node. The first node can indicate a clinical condition, and the second node can indicate a clinical conclusion. Then, a clinical conclusion can be determined based on the at least one path in response that the at least one path matching the at least one clinical condition is searched out.

Abstract: An analysis apparatus comprises: a generation module configured to generate a second piece of input data having a weight for a first feature item of a patient based on: a first piece of input data relating to the first feature item; a second feature item relating to a transition to a prediction target in a clinical pathway relating to a process for diagnosis or treatment; and a clinical terminology indicating relevance between medical terms; a neural network configured to output, when being supplied with the first piece of input data and the second piece of input data generated, a prediction result for the prediction target in the clinical pathway and importance of the first feature item; an edit module configured to edit the clinical pathway based on the prediction result and the importance output from the neural network; and an output module configured to output an edit result.

Abstract: A subject is prescribed short and long acting insulin medicament regimens. When a qualified fasting event occurs, the basal insulin sensitivity estimate of the subject is updated using (i) an expected fasting blood glucose level based upon the long acting insulin medicament dosing specified by the long acting regimen during the fasting event, (ii) glucose measurements contemporaneous with the fasting event and (iii) a prior insulin sensitivity factor. A basal insulin sensitivity factor curve is calculated from the updated basal insulin sensitivity estimate. A bolus insulin sensitivity estimate of the subject is updated upon occurrence of a correction bolus with a short acting insulin medicament using (i) an expected blood glucose level based upon the correction bolus, (ii) glucose measurements after occurrence of the correction bolus, and (iii) a prior insulin sensitivity factor. A bolus insulin sensitivity factor curve is calculated from the updated bolus insulin sensitivity estimate.

Abstract: Methods, systems, and computer-readable media are provided for analyzing amounts of time spent by clinicians caring for patients. Clinician locations, patient locations, patient data, and clinician electronic health record activity may be used to facilitate generation of one or more predictive models. Such predictive models will provide, among other things, a decision support tool for scheduling patient-clinician appointments to minimize, at least partially, patient wait times.

Abstract: Systems and methods are disclosed for receiving one or more digital images associated with a tissue specimen, a related case, a patient, and/or a plurality of clinical information, determining one or more of a prediction, a recommendation, and/or a plurality of data for the one or more digital images using a machine learning system, the machine learning system having been trained using a plurality of training images, to predict a biomarker and a plurality of genomic panel elements, and determining, based on the prediction, the recommendation, and/or the plurality of data, whether to log an output and at least one visualization region as part of a case history within a clinical reporting system.

Abstract: A computer system monitors users to capture contextual and environmental data for managing adverse events of those users. A level of risk for occurrence of an adverse event from performing a medical related activity is determined based on the medical related activity, a medical profile, and a risk profile of the user. The user is monitored to capture environmental and contextual information for the adverse event. The captured information is stored to associate the captured information with the adverse event. In response to occurrence of the adverse event, the user is prompted to provide information pertaining to conditions surrounding the adverse event. The stored information for the adverse event is updated with the user-provided information, and is transmitted to a provider associated with the medical related activity. Embodiments of the present invention further include a method and program product for managing adverse events in substantially the same manner described above.

Abstract: A computing system receives a plurality of medical perspectives for each medical treatment option of a plurality of medical treatment options. A machine learning model assigns a weight to each medical perspective for each medical treatment option by determining how often a care provider has agreed with each perspective within the plurality of medical perspectives. The computing system receives a medical treatment option ranking for each of the medical perspectives. The computing system generates a score for each medical perspective as applied to each medical treatment option based on a combination of the weight and the ranking for each medical perspective. The computing system aggregates the scores across the plurality of medical perspectives into an overall score for each medical treatment option.