Abstract: The invention provides for a means of aligning a first virtual object with a second virtual object that is different from the first virtual object within a scene volume in a 3D virtual space. The method includes performing a 3D scan of the user's head to get the first virtual object. The second virtual object comprises a 3D model of a mask. The method further determining a location of a first surface point on a surface of the first virtual object based on a first ray casting of the first virtual object, and determining a location of a second surface point on a surface of the second virtual object based on a second ray casting of the second virtual object. The second surface point has a desired positional relationship with respect to the first surface point. The first ray casting originates from outside the scene volume and the second ray casting originates from inside the scene volume.

Abstract: A method for optimal design of experiments for joint model selection and parametrization determination of a symbolic mathematical model includes: determining a prediction value for a given inquiry data point, functional form and parameterization for conducting an experiment relating to a system under investigation; assuming a set of input-output data pairs as a starting point in a model discovery process relating to the system under investigation; performing discovery of symbolic models minimizing complexity for a bounded misfit, or minimizing a misfit measure, subject to bounded complexity; determining a new data point through optimal experimental design that informs best as for the underlying symbolic models; and updating a posterior distribution, given results of the experiment relating to the system under investigation for the determined new data point to enable informed assessment among a plurality of functional forms and parameterizations. An apparatus configured to perform the method is also provided.

Abstract: Systems and methods are described for performing at least one of assessing, optimizing and/or controlling the performance of an Anaerobic Digestion (AD) plant. The system comprises a server that provides a user interface for allowing a user to enter user inputs to define various aspects of the AD plant operation and to view results of the simulation; a database for storing the inputs used for the simulation of the anaerobic digestion plant, the inputs including feedstock inputs, AD operational inputs, and simulation criteria; and a simulation engine that can be operated in an at least one of an off-line simulation mode for generating off-line simulator predictions, a near-line simulation mode for optimizing the performance of the system and an online mode for using machine learning to tune the performance of various models used in simulating the operation of the AD plant.

Abstract: A normal set of cells is characterized using flow cytometry. A centroid and radius are defined for a set of clusters in an n-dimensional space corresponding to a normal maturation for a cell lineage in the normal set of cells. A test set of cells is characterized using flow cytometry and the characterization is compared to the defined set of clusters. Support Vector Machine (SVM) subroutines are employed to identify reference populations of interest by generating multidimensional boundary definitions. These boundary definitions may be used to identify reference populations to use in defining or refining a centroid line or a radius or radii defining a set of normal clusters, and to characterize and compare a test set of cells to the defined set of normal clusters.

Abstract: Systems and methods for generating a 3D model of a dentition are disclosed herein. A method includes generating a first 3D model of a dentition including a plurality of model teeth. The method includes receiving at least one digital representation comprising patient teeth. The method includes determining a virtual camera parameter. The virtual camera parameter corresponds with a camera used to capture the digital representation. The method includes comparing, based on the virtual camera parameter, a first position of a model tooth with a position of a corresponding patient tooth of the digital representation. The method includes moving the model tooth from the first position to a second position. The second position is based on the position of the corresponding patient tooth. The method includes generating a second 3D model comprising the model tooth of the first 3D model in the second position.

Abstract: An automated method for determining a coagulation result of a biological sample is presented. The method includes obtaining a time series representing measurement data of a sample. The time series spans a period in which a clotting reaction is supposed to take place. The method includes obtaining a global model function configured to model measurement data of a sample in which a clotting reaction takes place. The global model function is configured to model the measurement data as a sigmoidal shape with at least one inflection point. The absolute value of the maximum curvature of the sigmoidal shape is larger on one side of the at least one inflection point than on the other side. The method includes fitting the model function to the time series representing measurement data to obtain a fitted model function and determining a coagulation result of the sample based on the fitted model function.

Abstract: An implant, a fitting plate suitable for placing of an implant, and a method for manufacturing an implant suitable for application on one or more bones.

Abstract: A method of generating a classifier includes a step of classifying each member of a development set of samples with a class label in a binary classification scheme with a first classifier; and generating a second classifier using a classifier development process with an input classifier development set being the members of the development set assigned one of the two class labels in the binary classification scheme by the first classifier. The second classifier stratifies the members of the set with an early label into two further sub-groups. We also describe identifying a plurality of different clinical sub-groups within the development set based on the clinical data and for each of the different clinical sub-groups, conducting a classifier generation process for each of the clinical sub-groups thereby generating clinical subgroup classifiers.

Abstract: A computer-implemented method for generating anatomical data associated with a musculoskeletal joint, the method comprising: receiving as input variation data representing change with time of a musculoskeletal joint of interest caused by a condition; receiving as input patient data representing the musculoskeletal joint of interest of a patient at a current time; and processing the variation data and the patient data to generate said anatomical data, wherein said anatomical data comprises data indicating the musculoskeletal joint of interest of the patient at a predetermined time different to the current time.

Abstract: The monitoring and control of bioprocesses is provided. The present disclosure provides the ability to generate generic calibration models, independent of cell line, using inline Raman probes to monitor changes in glucose, lactate, glutamate, ammonium, viable cell concentration (VCC), total cell concentration (TCC) and product concentration. Calibration models were developed from cell culture using two different CHOK1SV GS-KO™ cell lines producing different monoclonal antibodies (mAbs). Developed predictive models, qualified using an independent CHOK1SV GS-KO™ cell line not used in calibration, measured changes in glucose, lactate, ammonium, VCC, and TCC with minor prediction errors over the course of cell culture with minimal cell line dependence. The development of these generic models allows the application of spectroscopic PAT techniques in a clinical manufacturing environment, where processes are typically run once or twice in GMP manufacturing based on a common platform process.

Abstract: A system, method and program product for a mechanistic model search engine. A system is disclosed having: a search interface for receiving input including text and functions relating to mechanistic models; a source interface for crawling online sources for mechanistic model information, wherein the information sources include text, tables, graphs, and functions; a context analysis system that determines parameter-based details from text information; a parameter processing system that derives parameter-based details from functions; and a search algorithm that compares parameter-based details determined from the input against parameter-based details determined from the information sources to identify mechanistic model search results.

Abstract: A computer-implemented method for creating an activity-optimized cutting guides for surgical procedures includes receiving one or more pre-operative images depicting one or more anatomical joints of a patient, and creating a three-dimensional anatomical model of the one or more anatomical joints based on the one or more pre-operative images. One or more patient-specific anatomical measurements are determined based on the three-dimensional anatomical model. A statistical model of joint performance is applied to the patient-specific anatomical measurements to identify one or more cut angles for performing a surgical procedure. A patient-specific cutting guide is created that comprises one or more apertures positioned based on the one or more cut angles.

Abstract: A convolutional neural network predicts which regions of a tissue slice would be stained by a first stain by training a model to identify those regions based only on tissue stained by a second stain. Thereafter the first stain need not be used to mark cancerous regions on other tissue slices that are stained with the second stain. The training slice is stained with a first immunohistochemical stain and a second counterstain. A target region of an image of the training slice is identified using image analysis based on the first stain. A set of parameters for associated mathematical operations are optimized to train the model to classify pixels of the image as belonging to the target region based on the second stain but not on the first stain. The trained parameters are stored in a database and applied to other images of tissue not stained with the first stain.

Abstract: A system and method for streamlining inventory and ordering for certain surgical supplies. The method includes scanning, by an imaging device, a surgical site and receiving, by a processor communicatively coupled to the imaging device, data from the scan. The method also includes the processor analyzing the data, where the analyzing includes searching the data to identify predefined key features in the data that are parameters utilized by a Statistical Shape Model (SSM). The processor applies the SSM to generate a three dimensional replica of a predetermined portion of the surgical site. The processor also defines, based on the replica, at last one of: surgical planes or orientations. The processor then utilizes the replica and the surgical planes or orientations to select a solution.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: Emission imaging data are reconstructed to generate a low dose reconstructed image. Standardized uptake value (SUV) conversion (30) is applied to convert the low dose reconstructed image to a low dose SUV image. A neural network (46, 48) is applied to the low dose SUV image to generate an estimated full dose SUV image. Prior to applying the neural network the low dose reconstructed image or the low dose SUV image is filtered using a low pass filter (32). The neural network is trained on a set of training low dose SUV images and corresponding training full dose SUV images to transform the training low dose SUV images to match the corresponding training full dose SUV images, using a loss function having a mean square error loss component (34) and a loss component (36) that penalizes loss of image texture and/or a loss component (38) that promotes edge preservation.

Abstract: This disclosure relates to a computer assistant for a surgeon with a graphical representation of a dynamic knee score for a knee surgery. A processor receives computer tomography data of a current patient's knee and user input from the surgeon, the user input comprises an identifier of a knee implant. The processor then retrieves multiple machine learning model parameters indicative of a machine learning performed on historical patient records. For multiple values of a rotation of the tibial component and a slope of the tibial component the processor configures a post-operative kinematic model performs a kinematic simulation and estimates a current patient outcome by applying the machine learning model. Finally, the processor generates a shaded surface spanning the multiple values of a rotation of the tibial component and a slope of the tibial component on a user interface to graphically represent the estimated current patient outcome for each of the rotation and slope.

Abstract: A system and method for accelerating the calculations of free energy differences by automating FEP-path-decision-making and replacing the standard series of alchemical interpolations typically created by molecular dynamic (MD) simulations with voxelated interpolated states. A novel machine learning approach comprising a restricted variational autoencoder (ResVAE) is used which can reduce the computational-cost associated with interpolations by restricting the dimensions of a molecular latent space. The ResVAE generates a model based on flow-based transformations of a 3D-VAE latent point that is trained to maximize the log-likelihood of MD samples which enables the model to compute transformations more efficiently between molecules and also handle deletions of atoms more efficiently during iterative FEP calculation steps.

Abstract: A method and system for creating a custom-fit orthopedic cast comprises obtaining at least one measurements taken from at least one image of a body part, selecting a template cast, modifying the template cast according to the measurements taken from the at least one image to generate a custom cast model and rendering a custom cast based on the custom cast model.

Abstract: Methods and systems described herein are directed to viewpoint coordination of multiple users on artificial reality collaboration models. Multiple users can collaborate on 3D models in an artificial reality environment. Attention indicators can indicate to the other users where a user is looking or where the user is pointing. In some implementations, there is a central model that each user sees from her own perspective (e.g., in the center of a virtual table all users are seated around) and/or instances of the model that only an individual user sees or can manipulate. The user's attention indicators can be based on where the user is looking or pointing on the model instances. Additionally, attention indicators can be translated from a controlling user's perspective to a coordinate system defined by the model, which allows the indicators to be then presented in that model coordinate system for all users.

Abstract: A method for operating an apparatus for predicting confirmed cases of an infectious disease is provided. The method comprises predicting infectious disease information per country, including an infection risk per country, expected number of entrants per country, and number of imported cases per country, based on collected epidemic statistics data per country and inflow data between a corresponding country and a destination country, grouping two or more countries based on geographic or economic relevance, and correcting the infectious disease information per country of countries within a grouped group according to a contagion risk impact set depending on a correlation between the countries within the group, and predicting total number of imported cases flowing into the destination country by re-correcting the infectious disease information per country through applying a correlation for the confirmed cases of the infectious disease between groups to the infectious disease information per country.

Abstract: In a general aspect, input data for a computer process are preprocessed by a preprocessor unit that includes a quantum processor. In some aspects, a preprocessor unit obtains input data for a computer process that is configured to run on a computer processing unit. Randomized parameter values are computed for variable parameters of a quantum logic circuit based on the input data. A classical processor in the preprocessor unit computes the randomized parameter values from the input data and a set of random numbers. A quantum processor in the preprocessor unit produces quantum processor output data by executing the quantum logic circuit having the randomized parameter values assigned to the variable parameters. Preprocessed data generated based on the quantum processor output data are then provided as the input for the computer process configured to run on the computer processing unit.

Abstract: Infusion systems, infusion devices, and related patient monitoring systems and methods are provided. A method of monitoring a physiological condition of a patient involves providing, on a display device, a graphical user interface display depicting forecast values with respect to different time periods in the future and including graphical user interface elements to allow a user to adjust a characteristic of an event likely influence the physiological condition of the patient at a respective time period. In response to an adjustment to a graphical user interface element, the method continues by dynamically updating the forecast values on the graphical user interface display using a forecasting model associated with the patient.

Abstract: A system and method for patient health data prediction and analysis which utilizes an automated text mining tool to automatically format ingested electronic health record data to be added to a knowledge graph, which enriches the edges between nodes of the knowledge graph with fully interactive edge data, which can extract a subgraph of interest from the knowledge graph, and which analyzes the subgraph of interest to generate a set of variables that define the subgraph of interest. The system utilizes a knowledge graph and data analysis engine capabilities of the data platform to extract deeper insights based upon the enriched edge data.

Abstract: A system and method for converting medical images of a particular patient into high resolution, 3D dynamic and interactive images interacting with medical tools including medical devices by coupling a model of tissue dynamics and tool characteristics to the patient specific imagery for simulating a medical procedure in an accurate and dynamic manner. The method includes a tool to add and/or to adjust the dynamic image of tissues and ability to draw and add geometric shapes on the dynamic image of tissues. The system imports the 3D surgery plan (craniotomy, head position, approach etc.). The surgeon establishes multiple views, rotates and interacts with the navigation image to see behind pathology and vital structures. The surgeon can make structures such as tumors, vessels and tissue transparent to improve visualization and to be able to see behind the pathology. The System can warn on proximity of tools to specific anatomical structure.

Abstract: A method for evaluating an ophthalmic lens for a given wearer according to a visual performance parameter includes providing wearer's data for the given wearer. The method further includes providing a visual performance parameter tolerance range for the wearer. The method further includes providing an ophthalmic lens to be evaluated, the ophthalmic lens being characterized by opto-geometrical features. The method further includes computing a value of the visual performance parameter for the lens to be evaluated on the basis of a model. The method further includes evaluating the ophthalmic lens by comparing the computed value of the visual performance parameter with the visual performance parameter tolerance range.

Abstract: A computer-implemented method according to one embodiment includes identifying a textual document, determining a chemical reaction within the textual document, extracting a plurality of chemical terms from the chemical reaction, creating an annotation for the chemical reaction, utilizing the plurality of chemical terms, and storing a representation of the annotation for the chemical reaction.

Abstract: A method of training for welding through virtual reality (VR) provides a VR headset, a processing device, and a welding training tool. The processing device is communicably coupled with the VR headset and the hand-held welding training tool designed to simulate a real-world welding experience in VR. A virtual welding environment is displayed through the VR headset, and motion tracking input is received through the welding training tool. The user input is analyzed using an AI algorithm to evaluate user welding performance. User feedback devices such as sound and scent generation may be implemented in order to simulate a welding procedure. AI user feedback is implemented based on the welding performance to guide learning. Welding scenarios may be completed to train for welding in the virtual welding environment, and virtual currency may be awarded for gamification purposes. Multi-participant welding scenarios and immersive, objective-based, simulated real-world environments are further implemented.

Abstract: A tactile display device including a nodule having variable stiffness under a surface to provide a near-real feeling of palpation for a physician. The device utilizes granular jamming technology using pneumatic actuation to control a nodule that maintains its shape while allowing the modulation in stiffness. The nodule includes two hemispheres, a contact portion and an actuation portion, forming a sphere. The contact portion and the actuation portion include different thicknesses and/or materials, while the dimensions of the dimensions of the nodule are maintained. As such, a physician can utilize the device to identify the difference between a normal lump and an affected lump even if the shape of each lump appears to be the same. With the tactile display device, due to the different levels of stiffness, a physician can detect the severity of the lump.

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: A facility for processing a medical imaging image is described. The facility applies each of a number of constituent models making up an ensemble machine learning models to the image to produce a constituent model result that predicts a value for each pixel of the image. The facility aggregates the results produced by the constituent models of the plurality to determine a result of the ensemble machine learning model. For each of the pixels of the accessed image, the facility determines a measure of variation among the values predicted for the pixel among the constituent models. Facility determines a confidence measure for the ensemble machine learning model result based at least in part on for how many of the pixels of the accessed image a variation measure is determined that exceeds a variation threshold.

Abstract: Hybrid terrain-adaptive lower-extremity apparatus and methods that perform in a variety of different situations by detecting the terrain that is being traversed, and adapting to the detected terrain. In some embodiments, the ability to control the apparatus for each of these situations builds upon five basic capabilities: (1) determining the activity being performed; (2) dynamically controlling the characteristics of the apparatus based on the activity that is being performed; (3) dynamically driving the apparatus based on the activity that is being performed; (4) determining terrain texture irregularities (e.g., how sticky is the terrain, how slippery is the terrain, is the terrain coarse or smooth, does the terrain have any obstructions, such as rocks) and (5) a mechanical design of the apparatus that can respond to the dynamic control and dynamic drive.

Abstract: Provided are methods for estimating a Reserve Strength Ratio in a segment of a blood vessel or a lymphatic vessel.

Abstract: Techniques for evaluating dynamically modified plans are provided. A selection of a treatment plan template is received, where the treatment plan template specifies a plurality of treatment stages, where each treatment stage defines a plurality of treatment options. A plurality of modifications to the treatment plan template is generated. It is determined, for each respective modification of the plurality of modifications, whether the respective modification is permissible, based on one or more predefined institutional criteria. Upon determining that a first modification of the plurality of modifications is permissible, a first treatment plan is generated based on the first modification to the treatment plan template. Further, a first predicted efficacy measure is generated for the first treatment plan based on analyzing a knowledge graph. Finally, the first treatment plan is provided, along with at least an indication of the first predicted efficacy measure.

Abstract: Provided herein are methods for predicting chemotherapy benefit. The invention predicts chemotherapy benefit based on the expression analysis of biomarkers, e.g., RNA biomarker transcription analysis, taken from a tumor sample. The biomarker expression data can be combined with clinical variables, e.g., tumor size and nodal status, to generate a profile that predicts the benefit of including chemotherapy as a treatment decision.

Abstract: Methods, systems, and computer-readable media are provided for aggregating, partitioning, and storing healthcare data. Healthcare data is collected from various disparate healthcare data sources. The data is aggregated into batches of the same type of data. From here, the data is partitioned according to the data's originating healthcare data source. The aggregated and partitioned healthcare data is then stored in a long term storage data store. This system of storing healthcare data allows for efficient retrieval and processing by computing solutions that need access to batches of healthcare data. The system also reduces costs associated with storing data as duplicate storage is eliminated.

Abstract: The present invention provides a human-computer interactive rehabilitation system, which can automatically calculate rehabilitation strength suitable for the patient, so that it is not necessary to manually evaluate and adjust the parameter settings in human-computer interactive rehabilitation system when different patients use it. At the same time, the human-machine interactive rehabilitation system and the hospital end can track the rehabilitation status and intervene through the data platform at any time. The platform establishes a cloud community feedback and encouragement mechanism, and immediately transmits the rehabilitation results to the designated barriers of the patients, provides patient encouragement feedback, and strengthens the community interaction and linkage in the medical relationship.

Abstract: A method for calculating binding free energy, where the method includes a plurality of steps each including adding a distance restraint potential between a binding calculation target molecule and a target molecule, wherein the method is a method for calculating binding free energy between the binding calculation target molecule and the target molecule using a computer, and wherein anchor points of the binding calculation target molecule in the plurality of the steps are identical anchor points, and anchor points of the target molecule in the plurality of the steps are different anchor points.

Abstract: A method for intraoperatively planning and facilitating a revision arthroplasty procedure. The method includes capturing positions of a tracked probe as the tracked probe contacts an interface area between a bone and a primary implant component implanted on the bone, intraoperatively generating a virtual boundary corresponding to a portion of the interface area to be removed to detach the primary implant component from the bone using the positions of the tracked probe and without use of pre-operative medical imaging, facilitating removal of the primary implant component from the bone by providing a constraint on operation of a cutting tool while the cutting tool removes the portion of the interface area, the constraint based on a relationship between the cutting tool and the virtual boundary.

Abstract: During operation, the system obtains the time-series sensor signals, which were gathered from sensors in a monitored system. Next, the system classifies the time-series sensor signals into stair-stepped signals and un-stair-stepped signals. The system then replaces stair-stepped values in the stair-stepped signals with interpolated values determined from un-stair-stepped values in the stair-stepped signals. Next, the system divides the time-series sensor data into a training set and an estimation set. The system then trains an inferential model on the training set, and uses the trained inferential model to replace interpolated values in the estimation set with inferential estimates. Next, the system switches roles of the training and estimation sets to produce a new training set and a new estimation set. The system then trains the inferential model on the new training set, and uses the trained inferential model to replace interpolated values in the new estimation set with inferential estimates.

Abstract: Certain aspects relate to systems and techniques for surgical robotic arm setup. In one aspect, there is provided a system including a first robotic arm configured to manipulate a medical instrument, a processor, and a memory. The processor may be configured to: determine a minimum stroke length of the first robotic arm that allows advancing of the medical instrument by the first robotic arm to reach a target region from an access point via a path, determine a boundary for an initial pose of the first robotic arm based on the minimum stroke length and a mapping stored in the memory, and during an arm setup phase prior to performing a procedure, provide an indication of the boundary during movement of the first robotic arm.

Abstract: Various technologies relating to constructing an answer to a query are described herein, wherein the answer is in list form. The answer includes a header and a list element. A deep model receives content of a webpage that is deemed relevant to the query by a search engine and constructs the answer to the webpage upon receipt of the query.

Abstract: A system for providing images of a human scalp and associated information for assisting in hair transplant planning, the system includes a support and at least one camera selectively connectable to the support, the camera and/or the support being configured for acquiring at least one, preferably a plurality of scale calibrated overview images of the human scalp of a patient's head, preferably from different predefined angles, optical acquisition means, preferably a video-dermatoscope, being configured for acquiring a plurality of microscopic images within different regions of the scalp, a processing unit configured to process and/or analyse image data provided by the camera means and the optical acquisition means, in particular for measuring areas of the human scalp, identify and measure hair in microscopic images and/or quantitatively plan a hair transplant operation, wherein the processing unit comprises a user interface configured for interacting with a user.

Abstract: A method for the deconvolution of nucleic acid-containing substance mixtures using synthetically generated target nucleotide sequences. Starting from a plurality of nucleotides,, a plurality of different target nucleotide sequences (TNS) is generated according to a predetermined algorithm. At least one of the TNS generated is associated with at least one substance or substance combination and chemically coupled thereto. At least one substance mixture to be analysed and having at least two different TNS is provided and is sequenced according to a sequencing method., at the same time all TNS contained in the substance mixture are detected in a common sequence spectrum. To facilitate the deconvolution, the sequence spectra of a substance mixture should be deducted/subtracted from each other prior to and after a selection experiment.

Abstract: The present invention relates to peptides, proteins, nucleic acids and cells for use in immunotherapeutic methods. In particular, the present invention relates to the immunotherapy of cancer. The present invention furthermore relates to tumor-associated T-cell peptide epitopes, alone or in combination with other tumor-associated peptides that can for example serve as active pharmaceutical ingredients of vaccine compositions that stimulate anti-tumor immune responses, or to stimulate T cells ex vivo and transfer into patients. Peptides bound to molecules of the major histocompatibility complex (MHC), or peptides as such, can also be targets of antibodies, soluble T-cell receptors, and other binding molecules.

Abstract: The disclosure relates to digital twin of cardiovascular system called as cardiovascular model to generate synthetic Photoplethysmogram (PPG) signal pertaining to disease conditions. The conventional methods are stochastic model capable of generating statistically equivalent PPG signals by utilizing shape parameterization and a nonstationary model of PPG signal time evolution. But these technique generates only patient specific PPG signatures and do not correlate with pathophysiological changes. Further, these techniques like most synthetic data generation techniques lack interpretability. The cardiovascular model of the present disclosure is configured to generate the plurality of synthetic PPG signals corresponding to the plurality of disease conditions. The plurality of synthetic PPG signals can be used to tune Machine Learning algorithms. Further, the plurality of synthetic PPG signals can be utilized to understand, analyze and classify cardiovascular disease progression.

Abstract: Described herein is a discovery Platform Technology for analyzing a biological system or process (e.g., a disease condition, such as cancer) via model building.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, can be implemented to perform certain actions. The actions can include maintaining biological data related to multiple biological systems in a first format in a data repository, receiving a first selection of a biological system of the multiple biological systems for constructing a model that simulates a behavior of the biological system, retrieving a subset of data of the biological data that is associated with the first selection of the biological system, receiving a second selection of a modeling technique of the multiple modeling techniques for constructing the model, compiling the subset of biological data into configuration data of a second format that is specific to the modeling technique and that is different from the first format, and generating the model using the modeling technique and the configuration data.

Abstract: A computer-aided pre-operative planning tool with interactive surgeon interface for total knee replacement implements a method that allows implant size selection, implant positioning, and surgical cut planes estimation (with construction of corresponding surgical jig), based upon a series of coronal, axial and sagittal image slices of a patient's leg. Limb alignment and corresponding surgical cut planes are defined based upon joint anatomical-matching analysis to minimize joint wear and restore a pre-arthritic alignment (rather than an always fully neutral alignment). Using the interface, a surgeon has the option to adjust the varus/valgus alignment within recommended bounds between the pre-arthritic and fully neutral alignments. Implant size may be selected based on a best fit to the patient's leg obtained from analysis of the images.

Abstract: A method of utilizing a computing device to correct source data used in machine learning includes receiving, by the computing device, first data. The computing device corrects the source data via an application of a covariate shift to the source data based upon the first data where the covariate shift re-weighs the source data.