Abstract: Aspects described herein relate to identifying media items relevant to a selected subject matter including, for example, determining the subject matter of a first media item, which may comprise at least one of audio content or video content; determining the classification within an ontology of the subject matter of the first media item; analyzing the ontology to identify other subject matter related to the subject matter of the first media item; and performing a search for other media items relevant to the subject matter of the first media item as a function of at least the other related subject matter according to the ontology.

Abstract: A model-assisted system for identifying candidates for a cohort based on a biomarker may include at least one processor. The processor may be programmed to access a database from which information associated with a population of individuals can be derived; provide, to a generalized biomarker model, a first biomarker associated with a cohort, the generalized biomarker model being trained based on one or more second biomarkers using the information, wherein the first biomarker is different from the one or more second biomarkers; receive, from the generalized biomarker model, a first output indicating a first group of the population of individuals exceeding a first likelihood threshold of having been tested for the first biomarker; and determine, based on the first output, whether an individual from among the first group of the population of individuals is a candidate for the cohort.

Abstract: A model-assisted system for predicting survivability of a patient may include at least one processor. The processor may be programmed to access a database storing a medical record for the patient. The medical record may include at least one of structured and unstructured information relative to the patient and may lack a structured patient ECOG score. The processor may be further programmed to analyze at least one of the structured and unstructured information relative to the patient; based on the analysis, and in the absence of a structured ECOG score, generate a performance status prediction for the patient; and provide an output indicative of the predicted performance status. The analysis of at least one of the structured and unstructured information and the generation of the predicted performance status may be performed by at least one of a trained machine learning model or a natural language processing algorithm.

Abstract: An apparatus, method, system and computer-readable medium are provided for generating one or more descriptors that may potentially be associated with content, such as video or a segment of video. In some embodiments, a teaser for the content may be identified based on contextual similarity between words and/or phrases in the segment and one or more other segments, such as a previous segment. Text/characters may serve as a candidate descriptor(s). In some embodiments, one or more strings of characters or words may be compared with (pre-assigned) tags associated with the content, and if it is determined that the one or more strings or words match the tags within a threshold, the one or more strings or words may serve as a candidate descriptor(s). One or more candidate descriptor identification techniques may be combined.

Abstract: An apparatus, method, system and computer-readable medium are provided for generating one or more descriptors that may potentially be associated with content, such as video or a segment of video. In some embodiments, a teaser for the content may be identified based on contextual similarity between words and/or phrases in the segment and one or more other segments, such as a previous segment. In some embodiments, an optical character recognition (OCR) technique may be applied to the content, such as banners or graphics associated with the content in order to generate or identify OCR'd text or characters. The text/characters may serve as a candidate descriptor(s). In some embodiments, one or more strings of characters or words may be compared with (pre-assigned) tags associated with the content, and if it is determined that the one or more strings or words match the tags within a threshold, the one or more strings or words may serve as a candidate descriptor(s).

Abstract: A model-assisted system for predicting survivability of a patient may include at least one processor. The processor may be programmed to access a database storing a medical record for the patient. The medical record may include at least one of structured and unstructured information relative to the patient and may lack a structured patient ECOG score. The processor may be further programmed to analyze at least one of the structured and unstructured information relative to the patient; based on the analysis, and in the absence of a structured ECOG score, generate a performance status prediction for the patient; and provide an output indicative of the predicted performance status. The analysis of at least one of the structured and unstructured information and the generation of the predicted performance status may be performed by at least one of a trained machine learning model or a natural language processing algorithm.

Abstract: Aspects described herein relate to identifying media items relevant to a selected subject matter including, for example, determining the subject matter of a first media item, which may comprise at least one of audio content or video content; determining the classification within an ontology of the subject matter of the first media item; analyzing the ontology to identify other subject matter related to the subject matter of the first media item; and performing a search for other media items relevant to the subject matter of the first media item as a function of at least the other related subject matter according to the ontology.

Abstract: Aspects described herein relate to identifying media items relevant to a selected subject matter including, for example, determining the subject matter of a first media item, which may comprise at least one of audio content or video content; determining the classification within an ontology of the subject matter of the first media item; analyzing the ontology to identify other subject matter related to the subject matter of the first media item; and performing a search for other media items relevant to the subject matter of the first media item as a function of at least the other related subject matter according to the ontology.

Abstract: An apparatus, method, system and computer-readable medium are provided for generating one or more descriptors that may potentially be associated with content, such as video or a segment of video. In some embodiments, a teaser for the content may be identified based on contextual similarity between words and/or phrases in the segment and one or more other segments, such as a previous segment. In some embodiments, an optical character recognition (OCR) technique may be applied to the content, such as banners or graphics associated with the content in order to generate or identify OCR'd text or characters. The text/characters may serve as a candidate descriptor(s). In some embodiments, one or more strings of characters or words may be compared with (pre-assigned) tags associated with the content, and if it is determined that the one or more strings or words match the tags within a threshold, the one or more strings or words may serve as a candidate descriptor(s).

Abstract: An apparatus, method, system and computer-readable medium are provided for generating one or more descriptors that may potentially be associated with content, such as video or a segment of video. In some embodiments, a teaser for the content may be identified based on contextual similarity between words and/or phrases in the segment and one or more other segments, such as a previous segment. In some embodiments, an optical character recognition (OCR) technique may be applied to the content, such as banners or graphics associated with the content in order to generate or identify OCR'd text or characters. The text/characters may serve as a candidate descriptor(s). In some embodiments, one or more strings of characters or words may be compared with (pre-assigned) tags associated with the content, and if it is determined that the one or more strings or words match the tags within a threshold, the one or more strings or words may serve as a candidate descriptor(s).

Abstract: A model-assisted system for identifying candidates for a cohort based on a biomarker may include at least one processor. The processor may be programmed to access a database from which information associated with a population of individuals can be derived; provide, to a generalized biomarker model, a first biomarker associated with a cohort, the generalized biomarker model being trained based on one or more second biomarkers using the information, wherein the first biomarker is different from the one or more second biomarkers; receive, from the generalized biomarker model, a first output indicating a first group of the population of individuals exceeding a first likelihood threshold of having been tested for the first biomarker; and determine, based on the first output, whether an individual from among the first group of the population of individuals is a candidate for the cohort.

Abstract: A model-assisted system for predicting survivability of a patient may include at least one processor. The processor may be programmed to access a database storing a medical record for the patient. The medical record may include at least one of structured and unstructured information relative to the patient and may lack a structured patient ECOG score. The processor may be further programmed to analyze at least one of the structured and unstructured information relative to the patient; based on the analysis, and in the absence of a structured ECOG score, generate a performance status prediction for the patient; and provide an output indicative of the predicted performance status. The analysis of at least one of the structured and unstructured information and the generation of the predicted performance status may be performed by at least one of a trained machine learning model or a natural language processing algorithm.

Abstract: Aspects described herein relate to identifying media items relevant to a selected subject matter including, for example, determining the subject matter of a first media item, which may comprise at least one of audio content or video content; determining the classification within an ontology of the subject matter of the first media item; analyzing the ontology to identify other subject matter related to the subject matter of the first media item; and performing a search for other media items relevant to the subject matter of the first media item as a function of at least the other related subject matter according to the ontology.

Abstract: Content items may be segmented and labeled by a theme to provide information, such as audio or video, with greater functionality, accuracy and speed. The segments and other related information may be stored and made accessible to users through, for example, a search service and/or an on-demand service. Also provided is automatic segmentation that may include any one of receiving a textual description of a content item, determining themes within the textual description, determining relevance intervals corresponding to terms of the theme, filtering and/or merging the relevance intervals, and determining a total interval for each theme that represents one or more contextually-coherent segments of the content item.

Abstract: Aspects described herein relate to identifying media items relevant to a selected subject matter including, for example, determining the subject matter of a first media item, which may comprise at least one of audio content or video content; determining the classification within an ontology of the subject matter of the first media item; analyzing the ontology to identify other subject matter related to the subject matter of the first media item; and performing a search for other media items relevant to the subject matter of the first media item as a function of at least the other related subject matter according to the ontology.

Abstract: Content items may be segmented and labeled by a theme to provide information, such as audio or video, with greater functionality, accuracy and speed. The segments and other related information may be stored and made accessible to users through, for example, a search service and/or an on-demand service. Also provided is automatic segmentation that may include any one of receiving a textual description of a content item, determining themes within the textual description, determining relevance intervals corresponding to terms of the theme, filtering and/or merging the relevance intervals, and determining a total interval for each theme that represents one or more contextually-coherent segments of the content item.

Abstract: In various embodiments, methods and systems make a type of resource available via a target web page, based on the presence of resources of the same type being available on other pages visited by the traffic accessing the target web page. One or more resource history values are determined for a set of traffic flows in at least a portion of the traffic that accesses the target web page. Each traffic flow extends between the target web page and a respective web page with a resource profile for the specified type of resource. The resource profiles can be used to determine resource history values for the traffic flows. The target web page's resource profile for the specified type of resource can be established based on the resource history values. Based on the target web page's resource profile for the specified resource type, a resource of the specified type can be designated to be available on the target web page.

Abstract: Aspects described herein relate to identifying media items relevant to a selected subject matter including, for example, determining the subject matter of a first media item, which may comprise at least one of audio content or video content; determining the classification within an ontology of the subject matter of the first media item; analyzing the ontology to identify other subject matter related to the subject matter of the first media item; and performing a search for other media items relevant to the subject matter of the first media item as a function of at least the other related subject matter according to the ontology.

Abstract: In various embodiments, methods and systems make a type of resource available via a target web page, based on the presence of resources of the same type being available on other pages visited by the traffic accessing the target web page. One or more resource history values are determined for a set of traffic flows in at least a portion of the traffic that accesses the target web page. Each traffic flow extends between the target web page and a respective web page with a resource profile for the specified type of resource. The resource profiles can be used to determine resource history values for the traffic flows. The target web page's resource profile for the specified type of resource can be established based on the resource history values. Based on the target web page's resource profile for the specified resource type, a resource of the specified type can be designated to be available on the target web page.

Abstract: The invention pertains to methods, systems, and apparatus for identifying media items relevant to a selected subject matter, the method comprising determining the subject matter of a first media item, the first media item comprising at least one of audio content and video content, determining the classification within an ontology of the subject matter of the first media item, analyzing the ontology to identify other subject matter related to the subject matter of the first media item, and performing a search for other media items relevant to the subject matter of the first media item as a function of at least the other related subject matter according to the ontology.