Abstract: A non-transitory computer readable recording medium storing instructions to control a computer of an information processing apparatus that processes information obtained from a patient terminal connectable to a healthcare worker terminal and to an electronic prescription server that stores electronic prescription information and dispensing information, the instructions causing the computer to execute: obtaining, from the patient terminal, the dispensing information associated with the electronic prescription information; obtaining, from the patient terminal, medicine taking information on a patient; associating the dispensing information and the medicine taking information with each other and creating integrated information; and outputting the integrated information to the healthcare worker terminal or the patient terminal.

Abstract: Prescription administration system for administering prescriptions to a plurality of patients. One embodiment provides a prescription administration system including a medication tray having a plurality of prescription boxes. Each of the plurality of prescription boxes is configured to receive a plurality of medications corresponding to a single administration time. The prescription administration system also includes an electronic processor. The electronic processor is configured to receive, via a user interface, a selection of an administering unit and identify a prescription box corresponding to the administering unit from the plurality of prescription boxes. The electronic processor is also configured to receive identification information of a patient and determine whether the identification information of the patient corresponds to the prescription box.

Abstract: A system and method for assigning a cannabidiol point value and recommending cannabidiol-infused edibles based on biological parameters and activity information. The system and method assign a cannabidiol point value to a cannabidiol-infused edible, and then recommends and delivers a cannabidiol diet to a user based on the user's biological parameters and activity information. An algorithm converts the biological parameters and activity information of the user into a biological and activity point value. At least one cannabidiol-infused edible is assigned a cannabidiol point value. The user scans the cannabidiol-infused edible to ascertain cannabidiol point value. The algorithm derives a recommended cannabidiol dosage for the user based on the association of the cannabidiol point value with the biological and activity point value. The user monitors the cannabidiol point value and consumed cannabidiol-infused edibles on a portable communication device. The cannabidiol-infused edibles are delivered to the user.

Abstract: Systems and methods are disclosed for interacting with a prescription submission system, a cloud computing system, and a prescription processing system to transmit prescriptions to an optimal pharmacy based on user information. User information, a location, and a prescription including a treatment e.g., medicine) may be received from a user or a health care professional. A plurality of pharmacies may be identified based at least on availability of the treatment, each of the plurality of pharmacies meeting a location criterion based on the location. Treatment pricing may be identified for each of the identified plurality of pharmacies. The plurality of pharmacies and the corresponding pricing information may be transmitted to a computing device. A selected pharmacy from the plurality of pharmacies may be received, from the computing device, and, the prescription may be transmitted to be received at the selected pharmacy’s prescription processing system.

Abstract: A method may include obtaining pathway data associated with a medication delivery pathway for delivering medication to a patient, the medication delivery pathway including at least one of the following: at least one catheter, at least one lumen, at least one port, or any combination thereof; obtaining prescription data associated with (i) a medication prescribed for delivery to the patient and (ii) another medication delivered, being delivered, or prescribed to be delivered to the patient; determining, according to a rule set, based on the pathway data and the prescription data, a medication delivery pathway for delivery of the medication to the patient; and assigning the medication for delivery to the patient via the medication delivery pathway.

Abstract: Apparatuses and methods for training users of ambulatory medical devices. The methods relate to improving user interactions with the touchscreens of devices. In one embodiment there is an operating mode that records all user interactions along with various device parameters and allows the clinician to review the patient’s performance for the initial use period. Automated analysis software may be employed to analyze the data generated by the device. The results of the analysis may be used by the clinician to improve the patient and device interaction.

Abstract: A method for managing glucose levels of a patient under the supervision of a healthcare professional (HCP). The method includes obtaining patient information for the patient, the patient information comprising patient medication data, patient monitoring data, and patient characteristic data. The method also includes creating a patient risk profile based on the patient information. The method also includes determining a likelihood that the patient will experience hyperglycemic effects based on the patient risk profile. The method also includes determining an optimum treatment plan for the patient based on the patient risk profile and the likelihood that the patient will experience hyperglycemic effects. The method also includes executing the optimum treatment plan.

Abstract: The present disclosure relates to a device for handling medicament delivery devices and is to be used with a safety container, where the medicament delivery devices have information retaining elements having information that is unique to specific medicament delivery devices, and which medicament delivery devices are to be put in a safety container after use. The disclosed device has an information obtaining mechanism operably arranged to obtain information from the medicament delivery devices placed into the safety container.

Abstract: Systems, devices and methods are disclosed for a prescription-regulated software application and an associated medical device. In some aspects, a smart medicine-injection device (e.g., smart insulin pen) is configured to be in communication with a patient's companion device (e.g., smartphone) having a software application (prescription app) that serves the patient as a complimentary medical device to the smart medicine-injection device, in which only certain features and functionalities of the prescription app are fully operable based on device pairing with the smart medicine-injection device to unlock medical device capabilities only available to the patient through prescription.

Abstract: Disclosed includes a body surface device for diagnosing locations associated with electrical rhythm disorders to guide therapy. The device can sense electrical signals and determine multiple sites that may be operative in that patient. The patch may encompass the heart regions from where the heart rhythm disorder originates. The patch comprises an array of electrodes configured to detect electrical signals generated by a heart. A controller may determine the locations of interest based on detected electrical signals. The controller is configured to locate these regions relative to the surface patch. The system may be coupled to a sensor or therapy device inside the heart, to guide this device to a region of interest. The controller is further configured to instruct the operator to use the trigger or source information to treat the heart rhythm disorder in an individual using additional clinical data and methods for personalization such as machine learning.

Abstract: A virtual reality therapy system is described. The virtual reality system includes a virtual reality headset, a garment, and an electronic device. The garment having at least one sensor, the at least one sensor configured to generate sensor data based upon movement. The electronic device is in communication with the virtual reality headset and receives the sensor data, or data based on the sensor data. The electronic device projects a virtual reality environment to the virtual reality headset based upon data generated by the at least one sensor of the garment.

Abstract: A method for clinical target contouring in radiotherapy may include obtaining one or more target images of a subject. The subject may include a target region to which a radiation treatment is directed. The method may also include obtaining a target volume segmentation model having been trained according to a machine learning technique. The method may further include determining boundary information relating to a target volume, the target volume including at least part of the target region based on the one or more target images and the target volume segmentation model.

Abstract: Methods, computer-readable media, and systems for providing disease management. In one implementation, a system develops a treatment recommendation for a patient based on patient data. The system may receive patient data, execute a basic model of the physiological system of the patient to generate a modified model for the patient based on the patient data, perform a statistical analysis of the patient data to detect data excursions of the parameter values; use the modified model to determine factors causing the data excursions; and use the model to develop a treatment recommendation to ameliorate negative effects of the disease.

Abstract: Systems and methods for treating social communication disorder are provided. A system may include a digital apparatus, which may include a digital instruction generation unit configured to generate instructions in real-time or near-real-time for the user to follow to treat social communication disorder based on a mechanism of action (MOA) in and a therapeutic hypothesis for the social communication disorder, and an outcome collection unit configured to collect the user's execution outcomes of the digital instructions. The system may also include a healthcare provider portal for a healthcare provider to manage their patients and/or an administrative portal for an administrator to manage healthcare providers.

Abstract: A system for providing disability-tailored therapy to a user having a disability with a presentation of the disability-tailored therapy compliant with accessibility requirements such that the presentation is accessible to the user having the disability is provided. The system includes a memory, a processor coupled to the memory programed with executable instructions, and a user device. The executable instructions cause the processor to obtain a disability-tailored therapy session for the user having the disability based on the disability. The user device configured to receive an input form the user and present the disability-tailored therapy session. The input is user information comprising the disability. The presentation is configured to be accessible to the user having the disability.

Abstract: The present disclosure relates to an apparatus and a method for analyzing medical data based on unsupervised learning. By using a machine learning model based on an adversarial generative neural network to detect and notify anomalies in medical data, the present disclosure allows accurate and rapid reading, in addition to saving time and cost incurred by reading.

Abstract: An approach for prioritizing the review of medial image scans in a medical record review program may be provided. The approach may include analyzing one or more medical image, where each image scan is associated with a patient from a plurality of patients. The analysis of the medical image scan may be based on a machine learning algorithm. The approach may also include identifying an abnormal condition(s) from the analyzed medical scans, where the identified abnormal condition(s) is based on the analysis. The approach may further include prioritizing the identified abnormal condition(s) if the abnormal condition is an urgent condition. Additionally, the approach may include presenting a scaled down version of the prioritized medical scan within a mini viewer window within a medical record review program.

Abstract: A medical information processing device of an embodiment includes processing circuitry. The processing circuitry is configured to automatically select and execute an application to be executed on a medical image to be processed from among a plurality of applications on the basis of predetermined reference information, compare first information indicating execution conditions for each of the plurality of applications included in the reference information with second information indicating an imaging condition for the medical image, and cause a display to display a list of applications that have not been executed among the plurality of applications and a result of comparison between the first information and the second information.

Abstract: Methods and systems are provided for reconstructing images from measurement data using one or more deep neural networks according to a decimation strategy. In one embodiment, a method for reconstructing an image using measurement data comprises, receiving measurement data acquired by an imaging device, selecting a decimation strategy, producing a reconstructed image from the measurement data using the decimation strategy and one or more deep neural networks, and displaying the reconstructed image via a display device. By decimating measurement data to form one or more decimated measurement data arrays, a computational complexity of mapping the measurement data to image data may be reduced from O(N4), where N is the size of the measurement data, to O(M4), where M is the size of an individual decimated measurement data array, wherein M<N.

Abstract: Method, systems, and apparatus for receiving a request for appointment availability, wherein the request for appointment availability comprises one or more procedural codes; determining an aggregate appointment duration and provider type data based at least on the one or more procedural codes from a first mapping of procedural codes to procedural durations and a second mapping of procedural codes to provider type data; identifying a plurality of appointment constraints based at least on the request for appointment availability, the aggregate appointment duration, and the provider type data; and applying the plurality of appointment constraints to calendar availability data of a plurality of providers to generate a plurality of candidate appointment slots based at least on the plurality of appointment constraints.

Abstract: Method, systems, and apparatus for receiving appointment data about one or more appointments, wherein the appointment data comprises one or more procedural codes for each of the one or more appointments; generating an estimated amount of inventory used for each of the one or more appointments based at least on the one or more procedural codes; calculating a remaining amount of available inventory from the estimated amount of inventory used; generating a threshold for each supply in the remaining amount of available inventory based at least on historical purchase data for the supply, wherein the historical purchase data comprises a duration from order to arrival; determining, for a given supply, that the remaining amount of available inventory for the given supply is under the generated threshold; and in response to the determining, generating a notification for a user to purchase the given supply.

Abstract: Computer-implemented systems and methods automatically track the dynamic composition of a patient-care team by combining and harvesting information from at least two electronic audit trails: (1) a trail recording access to electronic medical records (EMR), e.g., read-access to patient data, electronic prescriptions and physician orders, etc., and (2) a trail recording electronic communications (email, text messages, etc.) regarding and referencing the patient.

Abstract: Embodiments disclosed herein may digitally enhance numeric and/or alphanumeric medical imaging codes using one or more enhancement metrics. The enhancement metrics may include, for example, complexity metric, modality metric, patient acuity metric, an add-on score, an additional item score, a technical resource expertise score or equipment capabilities score, one or more of which may be used generate an enhanced resource utilization value resulting in, comprehensive operational and financial performance metrics. The enhanced resource utilization value may more accurately reflect the actual performance medical imaging facilities used as the medical imaging industry standard compared to the conventional systems.

Abstract: In some embodiments, a system generates a map of a care facility. The system comprises one or more sensors coupled to a computing device and configured to generate sensor data corresponding to locations inside the care facility. The computing device is configured to: determine, for the locations, features of the care facility based on the sensor data; and generate, based on the features, the map of the care facility that includes the locations.

Abstract: Methods and systems for medical device diagnostics and reporting. One system including an electronic processor configured to receive a new medical device dataset associated with a medical device. The electronic processor is also configured to determine an operation classification of the medical device using a model utilizing training information. The training information includes a plurality of archived medical device datasets and an associated operation classification for each of the plurality of archived medical device datasets. The electronic processor is also configured determine an operation status of the medical device based on the operation classification. The electronic processor is also configured to generate and provide a notification based on at least the operation status of the medical device.

Abstract: A manipulator device management system can include a manipulator device comprising a plurality of manipulator arms and a control system. The control system can have one or more processors configured to perform operations comprising: selecting, for a first manipulator arm of the plurality of manipulator assemblies, a first assignment from a plurality of assignments available to the first manipulator arm; and causing the first manipulator arm to adopt the first assignment. The first assignment can be available to at least two manipulator arms of the plurality of manipulator arms. The first assignment can designate at least one operating parameter selected from the group consisting of a location for the first manipulator arm and a type of instrument to be used with the first manipulator arm.

Abstract: A medical system for removing an object in a body cavity, includes a display, and a controller connectable to a drive device configured to control a medical device operated by an operator to remove the object. The controller is configured to acquire device information indicating features of different types of first devices connectable to the medical device, acquire target information indicating characteristics of a target object to be removed, rank the first devices for removing the target object using the device information and the target information, and display on the display a list of the first devices according to the rank thereof.

Abstract: An implantable sensor device for monitoring patient conditions surrounding a surgical site is disclosed. The implantable sensor device comprises one or more sensors, a memory, and a controller. The implantable sensor device is configured to confirm activation of the implantable sensor device. Further, the implantable sensor device monitors the one or more sensors sensing the implanted device and stores the monitored data in the memory and sends the monitored data to the external device by establishing a connection with the external device, via a network interface. The implantable sensor device is further configured to monitor the stored data for the adverse event and perform an action to mitigate the risk of the life of the patient caused due to the adverse event.

Abstract: A computer-implemented method, computer program product and computing system for processing a medical assistance request from a requester; defining an incident location for the medical assistance request; assigning an autonomous drone to the medical assistance request, thus defining an assigned autonomous drone; and dispatching the assigned autonomous drone to the incident location.

Abstract: This disclosure provides systems, methods and apparatus for processing, transmitting and displaying data received from an analyte sensor, such as a glucose sensor. The system may include a display device with at least one input device. In response to movement of or along the input device, the display device may change a glucose data output parameter and update an output of the display device using the changed output parameter.

Abstract: A method for information overweight detection and intervention is described. The method includes training a statistical model to classify salient information that may be overweight by individuals to provide a trained statistical model. The method also includes collecting data from a user about the salient information experienced by the user or to which the user is exposed. The method further includes analyzing the salient information using the trained statistical model to identify and classify the salient information that the user may overweight to identify overweight information. The method also includes presenting one or more interventions to the user to prevent the user from overweighting the identified overweight information.

Abstract: Method, systems, and apparatus for generating a plurality of candidate patient procedures based at least on one or more procedural codes; determining, for each of the plurality of candidate patient procedures, a risk score for the candidate patient procedure using a machine-learning model trained on data comprising one or more procedure types, patient information, and frequency scores of procedural incidents for each procedure type, and severity scores of procedural incidents for each procedure type; determining, for each of the plurality of candidate patient procedures, a recommendation score for the candidate patient procedure based at least on insurance provider data for the patient in the candidate patient procedure, a mapping of the candidate patient procedure to revenue per procedure, and the risk score for the candidate patient procedure; and generating one or more appointment creation messages for distribution to a plurality of candidate patients based on the recommendation scores.

Abstract: A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: Methods of diagnosing a biological entity in a sample are disclosed. In one arrangement image data representing one or more images of a sample is received. Each image contains plural instances of a biological entity. Each of at least a subset of the instances have at least one optically detectable label attached to the instance. The image data is preprocessed to obtain preprocessed image data. The preprocessed image data is used in a trained machine learning system to diagnose the biological entity.

Abstract: A system comprising an assessment engine configured to asynchronously transmit assessment questions to a user and, in response, receive a plurality of personal data from a user. A behavior module communicatively coupled to the assessment engine and operable to generate a behavior profile associated with the user based, at least in part, on the plurality of personal data. The behavior profile configured to identify one or more addiction habits of the user and respective one or more triggers operable to induce the user to desire the one or more addiction habits. A plurality of sensors positioned proximate the user to provide real-time measurements of one or more biological conditions of the user body. A prediction module communicatively coupled to the plurality of sensors, the prediction module operable to predict occurrence of the one or more triggers based on the behavioral profile and the real-time measurements of the one or more biological conditions of the user body.

Abstract: A computer implemented cognitive state estimation method (10) comprising: receiving a recording of a user and at least one context primitive (11), each context primitive comprising a time series of context descriptors; extracting at least one behaviour primitive from the recording (12), each behaviour primitive comprising a time series of behaviour descriptors; producing a behaviour map from the at least one behaviour primitive (13); producing a context map from the at least one context primitive (14); and estimating a cognitive state of the user using data derived from the behaviour map and the context map (15).

Abstract: Systems and methods for rapid screening of signs and symptoms associated with disorders are disclosed. A processor or processing element in operable communication with one or more sensors is configured to detect physiological and movement changes associated with a disorder based on signals derived from sensor data generated by the one or more sensors as a user performs a set of predetermined scripted activities.

Abstract: A method of providing information for predicting the prognosis of breast reconstruction surgery and a system for predicting the prognosis of breast reconstruction surgery is provided. By using the method or system for providing information for predicting the prognosis of breast reconstruction surgery according to one specific example of the present invention, it is possible to predict the possibility of implant rupture in a subject who has undergone or is scheduled to undergo two-stage breast reconstruction surgery, and it is possible to prepare an appropriate treatment according to this prediction, and to adjust the interval between breast reconstruction surgeries so as to lower the possibility of implant rupture. In addition, it is possible to provide information so that an implant with a low possibility of rupture may be selected.

Abstract: A method of providing information to predict the prognosis of breast reconstruction surgery and a system for predicting the prognosis of breast reconstruction surgery is provided. By using a method or system for providing information to predict the prognosis of breast reconstruction surgery according to one specific example, it is possible to predict the occurrence of complications in a subject into which a tissue expander is inserted or scheduled to be inserted during a process of breast reconstruction surgery and to prepare appropriate treatment for the subject, and it is possible to provide information to aid in selecting a type of tissue expander with a low possibility of complication occurrence.

Abstract: Systems and methods are provided for monitoring health.

Abstract: There is provided detection of one or more life-threatening conditions with the help of a computerized model. A method for training a computerized model comprises receiving time-domain sample sequences of measurements of at least two biosignals from subjects; determining on the basis of computer-readable data from a subject database, information indicating timing of one or more life-threatening conditions of subjects; windowing the received time-domain sample sequences on the basis of a predefined window length; generating two-dimensional power spectral densities, 2D PSDs, of the windowed time-domain sample sequences; labeling the generated 2D PSDs to indicate a relationship to a life-threatening condition on the basis of the determined information indicating timing of one or more life-threatening conditions of the subjects; training a computerized model for detection of a life-threatening condition on the basis of the labeled 2D PSDs.

Abstract: Techniques are disclosed for using feature delineation to reduce the impact of machine learning cardiac arrhythmia detection on power consumption of medical devices. In one example, a medical device performs feature-based delineation of cardiac electrogram data sensed from a patient to obtain cardiac features indicative of an episode of arrhythmia in the patient. The medical device determines whether the cardiac features satisfy threshold criteria for application of a machine learning model for verifying the feature-based delineation of the cardiac electrogram data. In response to determining that the cardiac features satisfy the threshold criteria, the medical device applies the machine learning model to the sensed cardiac electrogram data to verify that the episode of arrhythmia has occurred or determine a classification of the episode of arrhythmia.

Abstract: A method is described for determining a disease progression and survival prognosis, at a succession of prediction times, for patients suffering from amyotrophic lateral sclerosis (ALS). The method comprises a step of defining a set of variables associated with the onset and progression of amyotrophic lateral sclerosis, comprising a first group of variables associated with the onset of amyotrophic lateral sclerosis (comprising at least the variables “patient sex”, “disease onset age”, “disease onset site”), a second group of dynamic time variables (comprising at least the variable “time elapsed since disease onset”), a third group of dynamic functional variables (comprising at least one of the variables breathing, swallowing, communicating, walking/self-care or at least one variable of a functional progression and/or severity scale of amyotrophic lateral sclerosis), and further at least one variable associated with survival.

Abstract: Disclosed are a disease prediction method, system and apparatus based on a multi-relation functional connectivity matrix. A Pearson correlation coefficient matrix and a DTW distance matrix are respectively calculated according to resting state functional magnetic resonance time series extracted from a brain atlas, the DTW distance matrix is converted in combination with the Pearson correlation coefficient matrix into a DTW? matrix which includes correlation degree and correlation direction information and whose numerical range is equivalent to the value range of a Pearson coefficient, and a functional connectivity matrix is obtained after weighted combination.

Abstract: Methods and systems for patient-specific post-surgery mortality prediction are disclosed. The methods and systems include: receiving a plurality of pre-operative factor indications for a patient; obtaining a first trained machine learning model and an interpretable model; applying the plurality of pre-operative factor indications to the first trained machine learning model to obtain a plurality of confidence values corresponding to the plurality of pre-operative factor indications; applying the plurality of confidence values to the interpretable model to obtain a plurality of interpretation indications, the plurality of interpretation indications corresponding to a subset of the plurality of pre-operative factor indications, the plurality of interpretation indications most contributing to mortality of the patient, the plurality of interpretation indications being specific to the patient; and outputting a survival probability of the patient based on the plurality of interpretation indications.

Abstract: In one embodiment, a computer-implemented method can receive, from a mobile computing device, a measurement-based care (MBC) assessment request from a patient. The method can asynchronously assess, using the application server, a plurality of MBC assessment data from the patient, wherein the plurality of MBC assessment data comprises passively collected data values, assessments, programmed heuristics, programmed rules, and model thresholds. The method can asynchronously generate, using a machine learning model and the application server, a plurality of vital sign values for the patient using the plurality of MBC assessment data from the patient. The method can asynchronously determine, using a machine learning model and the application server, stratification group data for the patient using the plurality of MBC assessment data from the patient. The method can send, to the mobile computing device, instructions for presenting a user interface comprising the stratification group data for the patient.

Abstract: A wearable device includes at least one physiological sensor configured to detect and/or measure physiological information from a subject over a period of time when the wearable device is worn by the subject, and a process or coupled to the sensor. The process or is configured to detect respective peaks in a physiological waveform representing the physiological information, compute probabilities for the respective peaks based on predetermined data indicative of one or more conditions, select a subset of the respective peaks based on the probabilities thereof as representing more accurate physiological information for the subject, and generate a physiological assessment of the subject based on the subset of the respective peaks that was selected. Related signal processing devices, methods of operation, and computer program products are also discussed.

Abstract: Proposed is an automated system providing an automatable long-term care risk mitigation structure associated with immediate care needs of risk-exposed individuals in case of becoming a long-term care-receiver. The system provides an automated multi-step trigger and detection cycle based on sensory measuring data for risk-exposed individuals thereby mitigating possibly occurring long-term care needs by means of the automated system based on a detected sufficient state of disability, possibly predetermined up-front amount parameters and an assigned care equity ratio associated with an asset. The state of disability of the risk-exposed individual is measurable by a definable set of risk-exposed individual measuring parameters.

Abstract: Method for modelling blood vessels includes: obtaining medical imaging data of the blood vessels; generating a three-dimensional personalized model of the blood vessels, based on the medical imaging data; generating a three-dimensional reference model of the blood vessels that reflects a state of healthy blood vessels that lack lesions, based on the medical imaging data or based on numerical reconstruction of the personalized model; performing a numerical simulation of blood flow for the same physical and boundary conditions in the personalized model and in the reference model, the simulation comprising determining conditions of blood flow at an inlet to the blood vessels model and calculating blood flow energy for the inlet and all outlets of the blood vessels model; comparing the blood flow energy measured for the personalized model and for the reference model; determining flow energy change indexes of the blood flow in the personalized model and the reference model.

Abstract: A method and an electronic device of checking drug interaction are provided. The method includes: generating a first odds ratio (OR) between a first drug combination and a hospitalization event, a second OR between a second drug combination and the hospitalization event, and a third OR between a third drug combination and the hospitalization event according to a plurality of medical records; generating a first fraction corresponding to a first drug according to the second OR; generating a second fraction corresponding to a second drug according to the third OR; and outputting the first drug combination in response to the first OR being greater than a first threshold, a sum of the first fraction and the second fraction being greater than a second threshold, and a quotient of the first fraction and the second fraction being less than a third threshold.