Abstract: An example computer-implemented method for providing diagnosis assistance includes receiving initial data associated with a diagnostic test result of a subject, selecting from among a plurality of machine-learning logic a machine-learning logic for execution based on a type of the diagnostic test result, determining by executing the machine-learning logic and based on the initial data a similarity between the initial data and diagnostic test result data stored in a database, based on the similarity between the initial data and the diagnostic test result data being within a similarity threshold providing an inquiry for display at the remote computing device to solicit additional information useful to resolve the undetermined outlier, receiving input data from the remote computing device in response to the inquiry, and storing the input data in the database.

Abstract: A method and system for generating a protein sequence is implemented using a computer-implemented neural network. An empty or partially filed sequence of node elements, representing amino acid positions of the protein sequence, and an edge index, having edge elements defining physical interaction between amino acid positions, are received. The computer-implemented neural network operates to determine enhanced edge attribute values for edge elements of the edge index and enhanced amino acid values for node elements of the sequence. Amino acid values are generated for elements of the partially filed sequence having missing values.

Abstract: In an aspect, a system for determining a liquid level in a drug delivery device is presented. The system includes a first spring and a second spring positioned adjacent the first spring. The system includes a rod configured to compress at least the first spring and contact the second spring. The system includes a sensing element in communication with the first spring and the second spring. The sensing element is configured to detect a difference in voltage of at least the first spring. A difference in voltage of at least the first spring corresponds to an amount of liquid drug of the drug delivery device.

Abstract: An artificial intelligence-based system comprises an input preparation module that accesses a sequence database and generates an input base sequence. The input base sequence comprises a target base sequence with target bases, wherein the target base sequence is flanked by a right base sequence with downstream context bases, and a left base sequence with upstream context bases. A sequence-to-sequence model processes the input base sequence and generates an alternative representation of the input base sequence. An output module processes the alternative representation of the input base sequence and produces at least one per-base output for each of the target bases in the target base sequence. The per-base output specifies, for a corresponding target base, signal levels of a plurality of epigenetic tracks.

Abstract: Techniques described herein are directed to determining that multimedia content displays a representation of an item offered for sale (1) at a first timestamp and (2) at a first location relative to a viewable window of a user device; generating an interactive element comprising an e-commerce tag interactable for purchase of the item; rendering, at the first timestamp, the interactive element on a first portion of the multimedia content and positioned relative to the representation of the item in a predetermined spatial configuration in the viewable window; rendering, at a second timestamp, the interactive element on a second portion of the multimedia content and positioned relative to the representation in the same spatial configuration; detecting an interaction with the interactive element; and based on detecting the interaction, displaying a graphical user interface configured to allow the user to purchase the item.

Abstract: The disclosure relates to analysing genetic data. In one arrangement, a method operates on input data comprising strengths of association between one or more phenotypes including a target phenotype and a plurality of genetic variants. A fine-mapping algorithm is applied to all or a subset of the input data to identify one or more independent phenotype-variant associations. A set of one or more fine-mapped variants is identified for each association. A fine-mapping predictive model is calculated on the basis of the input data and the set of fine-mapped variants. The effect on the target phenotype of the set of fine-mapped variants is subtracted from the input data to obtain residual association data. A machine learning algorithm is applied to the residual association data to identify further predictive correlations between the target phenotype and the plurality of genetic variants.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a heterogenous network and determining diffusion weights of scientific evidence in the heterogenous network. The computer obtains clinical data associated with a clinical network of healthcare providers and scientific data associated with a scientific network of scientists. The computer generates a first graph network representing the clinical network and a second graph network representing the scientific network. The computer identifies a first set of target nodes in the first graph network representing clinical leaders, and a second set of target nodes in the second graph network representing scientific leaders. The computer predicts links connecting the first graph network to the second graph network and generates a heterogenous network with nodes from the first graph network and from the second graph network, and the links connecting the first graph network to the second graph network.

Abstract: A medical device, a system including a medical device and a supply facility, and a method for operating the system are provided. For a planned activity, the medical device at least temporarily needs a resource from the supply facility. The medical device has a device control system and an interface for communication with the supply facility regarding the resource. In a notification, the medical device notifies the supply facility of a requirement for a resource.

Abstract: Aspects as described herein are directed to providing an enhanced user experience for consuming content on a computing device. Secondary computing devices, such as handheld smartphones and tablet-style computers, may be identified by a primary computing device, such as a set-top box. The secondary computing devices may be configured to receive actionable instructions from the primary computing device. An actionable event associated with content being outputted to a user via the primary computing device may be determined and an actionable instruction may be transmitted to the secondary computing device in response to the determined actionable event.

Abstract: A processing module may be centralized and coupled to multiple inputs from customers, and behave deterministically, e.g., programmed to depend on state, inputs and outputs. The rapid speed of automated trading systems implementing such a centralized, deterministic module, where all users can access a central limit order object, can quickly result in an object state that does not reflect a true consensus or desirable state. Accordingly the resulting problem is a problem arising in computer systems due in part to the high speeds of computer systems. The solutions disclosed herein are, in one embodiment, implemented as automatic responses and actions by a computing system.

Abstract: The present disclosure is directed to systems and methods of providing content. A server can generate a request for a push content item for an account identifier linked with a computing device. The server can establish a push auction for the account identifier with multiple candidate push content items. The server can determine an auction score for each candidate push content item and select a push content item therefrom based on the auction score. The server can determine a parameter for the account identifier and control delivery of the selected push content item based on a delivery control policy. The server can compare a value of the parameter with a threshold value to authorize the push content item. The server can provide the selected and authorized push content item for presentation in a push content slot via the computing device linked to the account identifier.

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 diagnostic tool includes a sensor for capturing at least one biosignal produced by a patient's heart and a computer device that implements a neural network iteratively trained via machine learning to generate a prediction about a heart condition of the patient. After the neural network is trained, the computer device can convert the at least one biosignal to a multi-dimensional input matrix for the deep neural network generated from a number (N) of biosignals captured by the sensor. The computer device then processes the multi-dimensional input matrix through the deep neural network, which subsequently outputs the prediction about the heart condition of the patient.

Abstract: A prediction system includes: a terminal; and a processor, communicatively coupled to the processor. The processor is configured to: acquire medical treatment information including images captured at at least one of before, during, immediately after, and after a predetermined period from treatment of a patient with a symptom of a vascular disease; classify a condition of the patient based on a classification image; learn the medical treatment information in association with the condition of the patient; and predict at least one of a treatment effect and a prognosis when treatment intervention is performed for the patient based on a learning result.

Abstract: Apparatuses, systems, and methods relate to technology to receive a user request from a user device, identify that a plurality of questions is available for presentation on the user device based on the user request and select a first question from the plurality of questions. The technology transmits the first question to the user device, receives a first user reply from the user device, where the first user reply is an answer to the first question and selects a second question from the plurality of questions based on the first user reply. The technology transmits the second question to the user device, receives a second user reply from the user device, where the second user reply is an answer to the second question, determines a user suggestion based on the first and second user replies, and transmits the user suggestion to the user device.

Abstract: The motion sickness estimation device includes an opening and closing detection unit configured to detect an opening/closing state of an eye of a vehicle occupant, a face direction estimation unit configured to estimate an orientation of a face of the occupant, and an occupant state estimation unit configured to calculate a traveling speed of the motion sickness with respect to the occupant based on the opening/closing state of the eye and the orientation of the face.

Abstract: The invention relates to a device for using individual data from networked medical devices for a simple and safe patient-specific equipment setting of an insufflator.

Abstract: Aspects of the present disclosure are directed to a cognition analysis and response system that can A) generate machine learning training data and use it to build a cognitive impairment machine learning model; B) identify cognitive impairments by applying the cognitive impairment machine learning model and performing a false positive/false negative analysis; and C) apply various automated adaptive measures for users with identified cognitive impairment. The cognition analysis and response system can apply the cognitive impairment machine learning model and can analyze these results to identify false positive and false negative cognitive impairment determinations by analyzing result confidence values, determining whether the result matches an expected progression of cognitive impairment, and/or analyzing external factors which may have caused incorrect results.

Abstract: Methods and systems for determining an expected disease treatment outcome upon treating a subject, methods and devices for selecting a treatment option for the subject, and methods of treating a subject for a disease, are described herein. The method can include receiving a plurality of subject characteristics for the subject; accessing a tree-based model corresponding to a treatment option for the disease, wherein the tree-based model is generated based on a plurality of prior patient characteristics and an associated treatment outcome for the corresponding treatment option; and determining from the plurality of subject characteristics and the tree-based model, an expected treatment outcome for the subject if the subject were treated with the corresponding treatment option.

Abstract: The present disclosure provides systems and methods for machine learning classification and assessment of disease based on gene expression data. In an aspect, a method for determining a disease state of a subject may comprise: (a) assaying a biological sample obtained or derived from the subject to produce a data set comprising gene expression measurements of the biological sample at each of a plurality of disease-associated genomic loci; (b) computer processing the data set to determine the disease state of the subject; and (c) electronically outputting a report indicative of the disease state of the subject. In some embodiments, the plurality of disease-associated genomic loci comprises single nucleotide polymorphisms (SNPs). In some embodiments, the disease comprises a lupus condition. In some embodiments, the disease comprises cardiovascular disease (CVD).