Abstract: Systems and methods disclosed include identifying a topic and a perspective of an input text to be sent to a receiver, determining a receiver perspective based on the topic of the input text and a receiver persona associated with the receiver, determining, by comparing the perspective of the input text and the perspective of the receiver, whether the input text includes a language having an offensive probability beyond an offensive probability threshold, after determining that the input text includes the language having the offensive probability beyond the offensive probability threshold, providing an option to modify the input text on a user interface of the sender, and modifying the input text to have the offensive probability below the offensive probability threshold when the option is selected.

Abstract: Systems and methods are disclosed for processing digital images to predict at least one continuous value comprising receiving one or more digital medical images, determining whether the one or more digital medical images includes at least one salient region, upon determining that the one or more digital medical images includes the at least one salient region, predicting, by a trained machine learning system, at least one continuous value corresponding to the at least one salient region, and outputting the at least one continuous value to an electronic storage device and/or display.

Abstract: A method for calibrating fluorospectrometric measurements obtained on a spectrometric device is disclosed. Calibration methods of this disclosure utilizes non-fluorescent emissions of water, primarily Raman scattering signals of water, as a calibration reference. For aqueous samples containing minute amounts of fluorescent analytes, the spectrometric measurements of samples obtained will contain both fluorescent emission and non-fluorescent emission, including water Raman scattering. Calibration factors based on the water Raman peaks are provided. Spectra of samples may be compared to each other by calibrating the spectral readings against the calibration factors. Also disclosed are apparatus useful for performing the calibration methods, including lens array for enhancing the optics of spectrometric measurements and water Raman calibration methods, spectrometric devices configured to perform the calibration methods, and computer-readable medium encoding the calibration method.

Abstract: Disclosed are systems and methods that address the limitations of current code completion techniques, generate multiple levels of syntactically complete code completions, each level of syntactically complete code completion based upon and dependent upon an acceptance of a prior level syntactically complete code completion. A first level syntactically complete code completion may be presented as a suggestion for inclusion in a code and each additional level of syntactically complete code completions in the sequence maintained in a cache so that the next level syntactically complete code completion can be presented immediately upon acceptance of the currently presented syntactically complete code completion.

Abstract: Systems and methods are described herein for processing electronic medical images to predict a biomarker's presence, including receiving one or more digital medical images, the one or more digital medical images being of at least one pathology specimen associated with a patient. A machine learning system may determine a biomarker expression level prediction for the one or more digital medical images. The biomarker expression level prediction may be based on a determined transcriptomic score and protein expression score for the one or more digital medical images. A slide overlay indicating a region of tissue on the one or more digital medical images that is most likely to contribute to the slide level biomarker expression prediction may be generated.

Abstract: Disclosed are systems and methods for processing at least one digital medical image to predict a first biomarker, including receiving the at least one digital medical image of one or more tissues of a patient, the at least one digital medical image including a plurality of tiles, analyzing, via a foundation model, the plurality of tiles to determine an embedding vector for each of the plurality of tiles, the foundation model having been trained to predict embedding vectors at a tile-level based on a plurality of digital medical images, and analyzing, via an aggregator model, the embedding vector for each of the plurality of tiles to predict the first biomarker of the digital medical image, wherein the aggregator model includes an attention mechanism configured to aggregate the embedding vector for each of the plurality of tiles into at least one slide-level prediction.

Abstract: A system and method for configuring a device includes using a machine learning model to generate a user behavior model based on user behavior data. The user behavior data may include time series data collected from user interactions with a first device, and the machine learning model may include a classification model configured to classify the user behavior data into the one or more classifications. A mapping may be created by training a machine learning model, using user behavior models from a plurality of users and device settings from the plurality of users, to identify one or more relationships between device settings and classifications of the user behavior data. The system and method configures one or more settings of a second device based on the user behavior model and the mapping.

Abstract: Provided herein are certain compounds and imaging agents useful for detecting a disease or condition associated with protein aggregation, compositions thereof, and methods of their use.

Abstract: A method for processing electronic medical images may include receiving an initial whole slide image of a pathology specimen, receiving information about slide quality aspects to modify, and generating a synthetic whole slide image by applying a machine learning model to modify the received initial whole slide image according to the received information. The pathology specimen may be associated with a patient. The synthetic whole slide image may have a reduced quality as compared to the initial whole slide image.

Abstract: A method implemented by a processor of a device, the method including determining one or more user values, determining a prompt requiring a decision, and receiving a user selection to one or more choice options related to the one or more user values and pertaining to the prompt requiring a decision. The method further includes comparing the user selection to a risk-neutral utility function and assessing a risk of a potential decision based on the comparison.

Abstract: Code completion suggestions may be proactively obtained and validated. An event that triggers obtaining a code completion suggestion for inclusion in a code file being edited using an integrated development environment may be detected. The code completion suggestion may be obtained. The characters of the code completion suggestion may be compared with characters added to the code file after the detection of the event that triggered obtaining the code completion suggestion to determine whether the code completion suggestion is valid. A valid code completion suggestion may then be displayed.

Abstract: Systems and methods for processing digital medical images to infer metadata from those images are disclosed. In some aspects, digital medical images may be processed to infer metadata by receiving a plurality of digital medical images, receiving a prompt, the prompt being a request for a specific type of metadata to be inferred from the plurality of digital medical images, determining, using a trained foundation model, at least one feature descriptor from the plurality of digital medical images based on the prompt, and providing for output the at least one feature descriptor for each of the plurality of digital medical images.

Abstract: A computer-implemented method for report parsing using a large language model. The method includes receiving a plurality of raw reports; filtering the plurality of raw reports; extracting raw data from the plurality of raw reports; providing the extracted raw data to a large language model (LLM); providing a prompt to the LLM; receiving a response from the LLM, the response including data labels derived from the extracted raw data; validating the received response against the plurality of raw reports; and training a machine learning model using the received response.

Abstract: Systems and methods for selecting a channel of communication based on a type of thinking employed by a user for a task are disclosed. The systems and methods include determining that a user is employing System 1 type thinking or System 2 type thinking for the task based on one or more properties of the task, one or more properties of the user, and a state of the user based on physiological response data from one or more physiological sensors monitoring the user, and implementing a channel of communication to utilize for the task that corresponds to a determined type of thinking the user is employing for the task.

Abstract: Systems and methods described herein are directed to implementations that facilitate individuals to collect, store, and automatically extract procedural knowledge from their messaging interactions with collaborative groups. Example implementations involve chat interfaces to communicate and add the capability to tag text and media to organize content. Example implementations also add a new thread-like structure to the previously only linear time-line of a chat. Knowledge from the chat can then be extracted automatically into a high-quality multimedia document.

Abstract: A method for processing electronic medical images may include receiving an initial whole slide image of a pathology specimen, receiving information about slide quality aspects to modify, and generating a synthetic whole slide image by applying a machine learning model to modify the received initial whole slide image according to the received information. The pathology specimen may be associated with a patient. The synthetic whole slide image may have a reduced quality as compared to the initial whole slide image.

Abstract: A system for providing code suggestions according to licensing criteria is described. The system comprises computing devices that implement a code suggestion service. The code suggestion service receives a request that specifies licensing criteria via an interface of the code suggestion service. The code suggestion service determines respective licenses for respective source code files according to a source code attribution database from parsing the plurality of source code files that are applicable to the plurality of source code files. The code suggestion service generates a set of candidate code suggestions based, at least in part, on the plurality of source code files. The code suggestion service determines code suggestions from the set of candidate code suggestions that satisfy the licensing criteria based on the respective licenses. The code suggestion service provides the code suggestions determined from the set of candidate source code files that satisfy the licensing criteria.

Abstract: Systems and methods described herein are directed to implementations that facilitate individuals to collect, store, and automatically extract procedural knowledge from their messaging interactions with collaborative groups. Example implementations involve chat interfaces to communicate and add the capability to tag text and media to organize content. Example implementations also add a new thread-like structure to the previously only linear time-line of a chat. Knowledge from the chat can then be extracted automatically into a high-quality multimedia document.

Abstract: Systems and methods are disclosed for processing digital images to predict at least one continuous value comprising receiving one or more digital medical images, determining whether the one or more digital medical images includes at least one salient region, upon determining that the one or more digital medical images includes the at least one salient region, predicting, by a trained machine learning system, at least one continuous value corresponding to the at least one salient region, and outputting the at least one continuous value to an electronic storage device and/or display.

Abstract: A system for providing code suggestions according to licensing criteria is described. The system comprises computing devices that implement a code suggestion service. The code suggestion service receives a request that specifies licensing criteria via an interface of the code suggestion service. The code suggestion service determines respective licenses for respective source code files according to a source code attribution database from parsing the plurality of source code files that are applicable to the plurality of source code files. The code suggestion service generates a set of candidate code suggestions based, at least in part, on the plurality of source code files. The code suggestion service determines code suggestions from the set of candidate code suggestions that satisfy the licensing criteria based on the respective licenses. The code suggestion service provides the code suggestions determined from the set of candidate source code files that satisfy the licensing criteria.