Abstract: A method, system and apparatus of for guiding a physically impaired individual during an emergency, including receiving emergency data, determining or predicting the reactions of other people in response to the emergency data, interpreting in real-time the reactions of the other people to physically impaired person according to the impaired person profile, determining a type and modality of aid services to the physically impaired, and prompting the physically impaired person through one or more devices for aid services.

Abstract: Improved quantification, detection, and characterizing of out-of-distribution (OOD) of a set of inputs that are generated by an alternative process such as anomalies, outliers, adversarial attacks, input errors can be provided with a combination of detection under perturbations and subset scanning algorithms. A first set of activations is extracted from nodes in a hidden layer of a neural network for an input. Noise is added to the input. A second set of activations is extracted from nodes in the hidden layer of a neural network for the noised input. A difference between the first set of activations and the second set of activations is determined. The difference is compared with a difference computed using in-distribution samples. Based on the comparison, an anomaly score for the input is determined. Multiple inputs can be processed. An iterative ascent algorithm finds out-of-distribution input and internal nodes with anomalous activations.

Abstract: In an aspect, during a presentation of a presentation material, viewers of the presentation material can be monitored. Based on the monitoring, new content can be determined for insertion into the presentation material. The new content can be automatically inserted to the presentation material in real time. In another aspect, during the presentation, a presenter of the presentation material can be monitored. The presenter's speech can be intercepted and analyzed to detect a level of confidence. Based on the detected level of confidence, the presenter's speech can be adjusted and the adjusted speech can be played back automatically, for example, in lieu of the presenter's original speech that is intercepted.

Abstract: An illustrative embodiment includes a method for detecting whether a given item within input data is anomalous. The method includes: extracting activations at respective nodes of an autoencoder trained on the data, the activations comprising activations at the respective nodes for the given item within the data and for one or more other items within the data; calculating p-values corresponding to the respective nodes, wherein the p-value for a given node represents a proportion of the activations at the given node for the other items which are greater than the activations at the given node for the given item; determining at least one score at least in part by scanning for a subset of the respective nodes which maximizes a statistical scoring function applied to the corresponding p-values; and providing a visualization of at least the given item within the input data to a human user.

Abstract: PI3K signalling is the most increased pathway in human cancers. The four isoforms of PI3K are thought to be activated by different redundant mechanisms leading to a common downstream signalling. The inventors questioned this concept, by mapping differential isoform-specific downstream signalling in response to their constant selective inhibition in pancreatic cancer, a disease currently without therapy. They identified common and specific signals activated by each PI3K isoform. These data make the rational for the development of highly selective PI3K isoform drugs used in combination, instead of compounds inhibiting all PI3Ks. In particular, the inventors showed that combined p110a and 110? inhibition is the most efficient strategy for pancreatic cancer patients.

Abstract: A computer system may create a language model corpus including multilingual alignment for training a combined language model and train (or pre-train) the combined language model. The computer system may create an adverse medication reaction corpus to include adverse medication reaction utterances and label an N-gram of an utterance in the adverse medication reaction utterances as a response to query, for multiple N-grams. The computer system may generate a code-mixed utterance model to perform code-mixed utterances in a turn by turn dialogue, by at least adding additional output layer including at least a start vector, language vector, and a query vector including at least the labeled N-gram, which are additional to the combined language model's predicted next words.

Abstract: A bias detection method, system, and computer program product include creating a context of an applicant based on a profile of the applicant and a context of a reviewer based on a profile of the reviewer, predicting a probability of overlapping data points between the applicant and the reviewer, building enriched embeddings for a deep learning model based on the context of the applicant, the context of the reviewer, the overlapping data points, and text from a review and a final decision by the reviewer, and calculating a bias score via a deep learning model run over the enriched embeddings.

Abstract: A Parkinson's disease treatment method, system, and computer program product, including administering a game to a user, monitoring a Parkinson's disease sign and a Parkinson's disease symptom based on a result of the user playing the game, adjusting treatment of the user depending on the Parkinson's sign and the Parkinson's symptom, and suggesting a tailored rehabilitation exercise for the user based on the treatment.

Abstract: An apparatus obtains participant sentiment data including at least one of: a text conversation between a participant and an investigator in a clinical trial; a video conversation between the participant and the investigator; and the participant's social network information; extracts and normalizes a sentiment score from the participant sentiment data; generates a compliance score for the participant by using a trained regressor on at least the sentiment score; compares the compliance score to a lower threshold and to a higher threshold; selects an action from a decision tree in response to the compliance score; and facilitates the action.

Abstract: A contextual hashtag generation method, system, and computer program product include receiving content from an online source, identifying a set of contextual indicators for the content, determining an entity-desired outcome for the content, and generating a hashtag for the content using the set of contextual indicators while maximizing the entity-desired outcome.

Abstract: A method, system and apparatus of for guiding a physically impaired individual during an emergency, including receiving emergency data, determining or predicting the reactions of other people in response to the emergency data, interpreting in real-time the reactions of the other people to physically impaired person according to the impaired person profile, determining a type and modality of aid services to the physically impaired, and prompting the physically impaired person through one or more devices for aid services.

Abstract: PI3K signalling is the most increased pathway in human cancers. The four isoforms of PI3K are thought to be activated by different redundant mechanisms leading to a common downstream signalling. However, the mutational pattern of PI3K pathway or its level of expression is not sufficient to predict the sensitivity to PI3K inhibitors. By identifying for the first time a phosphopeptide that predict the sensitivity to p110? and/or p110? inhibitors, the inventors provide insight in how to handle heterogeneity of PI3K expression patterns in tumoral samples for the choice of available PI3K-targetting drugs. Accordingly, the present relates to a phosphopeptide characterized by the amino acid sequence as set forth in SEQ ID NO:1 (PGTPSDHQSQEASQFER) wherein the threonine residue at position 3 is phosphorylated.

Abstract: A bias detection method, system, and computer program product include creating a context of an applicant based on a profile of the applicant and a context of a reviewer based on a profile of the reviewer, predicting a probability of overlapping data points between the applicant and the reviewer, building enriched embeddings for a deep learning model based on the context of the applicant, the context of the reviewer, the overlapping data points, and text from a review and a final decision by the reviewer, and calculating a bias score via a deep learning model run over the enriched embeddings.