Patents by Inventor Vivek Varma
Vivek Varma has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240139466Abstract: Provided herein is a medical device kit that includes a base sheet having an inner surface and an outer surface and a first base portion and a second base portion, the base sheet configurable between a folded state and an unfolded state. A first waste bin is secured to the first base portion on the inner surface and a second waste bin is secured to the second base portion on the inner surface. A plurality of pockets configured to retain medical supplies therein is attached to the first waste bin, the second waste, or both the first and second waste bins, on an outward facing surface thereof. A plurality of fastening devices is provided configured to secure the first base portion to the second base portion when the base sheet is in the folded state and to selectively seal shut the first waste bin and the second waste bin.Type: ApplicationFiled: November 2, 2022Publication date: May 2, 2024Inventors: Shishir Prasad, Rahul Malviya, Sudarsen Varma, Atharva Shetye, Aishwarya Landekar, Vivek K T
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Publication number: 20240143921Abstract: Techniques are described for training and/or utilizing sub-agent machine learning models to generate candidate dialog responses. In various implementations, a user-facing dialog agent (202, 302), or another component on its behalf, selects one of the candidate responses which is closest to user defined global priority objectives (318). Global priority objectives can include values (306) for a variety of dialog features such as emotion, confusion, objective-relatedness, personality, verbosity, etc. In various implementations, each machine learning model includes an encoder portion and a decoder portion. Each encoder portion and decoder portion can be a recurrent neural network (RNN) model, such as a RNN model that includes at least one memory layer, such as a long short-term memory (LSTM) layer.Type: ApplicationFiled: January 4, 2024Publication date: May 2, 2024Inventors: Vivek Varma DATLA, Sheikh Sadid AL HASAN, Aaditya PRAKASH, Oladimeji Feyisetan FARRI, Tilak Raj ARORA, Junyi LIU, Ashequl QADIR
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Publication number: 20240062005Abstract: A system (100) is extracting targeted medical information from clinical notes stored in memory (120). The system (100) includes a preprocessing module (120a) configured to retrieve from the memory (120) a sequence of clinical texts of electronic health records, and to tokenize the sequence of clinical texts to obtain a sequence of input tokens. The system (100) further includes a sequence to structure model module (120b) configured to transform, using a trained natural language based transformer, the sequence of input tokens into a sequence of structured output tokens. The system (100) further includes a post-processing unit (110) configured to obtain annotated text-label pairs of the clinical texts from the structure output tokens.Type: ApplicationFiled: August 8, 2023Publication date: February 22, 2024Inventors: Dongfang Xu, Ankur Sukhalal Padia, Kathy Mi Young Lee, Vadiraj Hombal, Vivek Varma
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Patent number: 11868720Abstract: Techniques are described for training and/or utilizing sub-agent machine learning models to generate candidate dialog responses. In various implementations, a user-facing dialog agent (202, 302), or another component on its behalf, selects one of the candidate responses which is closest to user defined global priority objectives (318). Global priority objectives can include values (306) for a variety of dialog features such as emotion, confusion, objective-relatedness, personality, verbosity, etc. In various implementations, each machine learning model includes an encoder portion and a decoder portion. Each encoder portion and decoder portion can be a recurrent neural network (RNN) model, such as a RNN model that includes at least one memory layer, such as a long short-term memory (LSTM) layer.Type: GrantFiled: January 16, 2020Date of Patent: January 9, 2024Assignee: KONINKLIJKE PHILIPS N.V.Inventors: Vivek Varma Datla, Sheikh Sadid Al Hasan, Aaditya Prakash, Oladimeji Feyisetan Farri, Tilak Raj Arora, Junyi Liu, Ashequl Qadir
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Patent number: 11822605Abstract: A system (1000) for automated question answering, including: semantic space (210) generated from a corpus of questions and answers; a user interface (1030) configured to receive a question; and a processor (1100) comprising: (i) a question decomposition engine (1050) configured to decompose the question into a domain, a keyword, and a focus word; (ii) a question similarity generator (1060) configured to identify one or more questions in a semantic space using the decomposed question; (iii) an answer extraction and ranking engine (1080) configured to: extract, from the semantic space, answers associated with the one or more identified questions; and identify one or more of the extracted answers as a best answer; and (iv) an answer tuning engine (1090) configured to fine-tune the identified best answer using one or more of the domain, keyword, and focus word; wherein the fine-tuned answer is provided to the user via the user interface.Type: GrantFiled: October 17, 2017Date of Patent: November 21, 2023Assignee: KONINKLIJKE PHILIPS N.V.Inventors: Vivek Varma Datla, Sheikh Sadid Al Hasan, Oladimeji Feyisetan Farri, Junyi Liu, Kathy Mi Young Lee, Ashequl Qadir, Adi Prakash
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Patent number: 11721335Abstract: A method for determining the answer to a query in a document, including: encoding, by an encoder, the query and the document; generating a query-aware context encodings G by a bidirectional attention system using the encoded query and the encoded document; performing a hierarchical self-attention on the query aware document by a hierarchical self-attention system by applying a word to word attention and a word to sentence attention mechanism resulting in a matrix M; and determining the starting word and the ending word of the answer in the document by a span detector based upon the matrix M.Type: GrantFiled: June 30, 2020Date of Patent: August 8, 2023Assignee: Koninklijke Philips N.V.Inventors: Tao Li, Sheikh Sadid Al Hasan, Vivek Varma Datla, Oladimeji Feyisetan Farri
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Publication number: 20230237330Abstract: Techniques are described herein for training and applying memory neural networks, such as “condensed” memory neural networks (“C-MemNN”) and/or “average” memory neural networks (“A-MemNN”). In various embodiments, the memory neural networks may be iteratively trained using training data in the form of free form clinical notes and clinical reference documents. In various embodiments, during each iteration of the training, a so-called “condensed” memory state may be generated and used as part of the next iteration. Once trained, a free form clinical note associated with a patient may be applied as input across the memory neural network to predict one or more diagnoses or outcomes of the patient.Type: ApplicationFiled: April 4, 2023Publication date: July 27, 2023Inventors: Aaditya PRAKASH, Sheikh Sadid AL HASAN, Oladimeji Feyisetan FARRI, Kathy Mi Young LEE, Vivek Varma DATLA, Ashequl QADIR, Junyi LIU
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Patent number: 11670420Abstract: Techniques are described herein for drawing conclusions using free form texts and external resources. In various embodiments, free form input data (202) may be segmented (504) into a plurality of input data segments. A first input data segment may be compared (510) with an external resource (304) to identify a first candidate conclusion. A reinforcement learning trained agent (310) may be applied (512) to make a first determination of whether to accept or reject the first candidate conclusion. Similar actions may be performed with a second input data segment to make a second determination of whether to accept or reject a second candidate conclusion. A final conclusion may be presented (522) based on the first and second determinations of the reinforcement learning trained agent with respect to at least the first candidate conclusion and the second candidate conclusion.Type: GrantFiled: April 3, 2018Date of Patent: June 6, 2023Assignee: Koninklijke Philips N.V.Inventors: Yuan Ling, Sheikh Sadid Al Hasan, Oladimeji Feyisetan Farri, Vivek Varma Datla, Junyi Liu
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Patent number: 11620506Abstract: Techniques are described herein for training and applying memory neural networks, such as “condensed” memory neural networks (“C-MemNN”) and/or “average” memory neural networks (“A-MemNN”). In various embodiments, the memory neural networks may be iteratively trained using training data in the form of free form clinical notes and clinical reference documents. In various embodiments, during each iteration of the training, a so-called “condensed” memory state may be generated and used as part of the next iteration. Once trained, a free form clinical note associated with a patient may be applied as input across the memory neural network to predict one or more diagnoses or outcomes of the patient.Type: GrantFiled: September 18, 2017Date of Patent: April 4, 2023Assignee: KONINKLIJKE PHILIPS N.V.Inventors: Aaditya Prakash, Sheikh Sadid AL Hasan, Oladimeji Feyisetan Farri, Kathy Mi Young Lee, Vivek Varma Datla, Ashequl Qadir, Junyi Liu
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Patent number: 11544587Abstract: A medical information retrieval system comprises a natural language processing system that processes a vocal user query to identify key words and phrases. These key words and phrases are provided to an inferencing engine that provides a set of knowledge-based inferences from medical knowledge sources, based on these key words and phrases. Thereafter, these knowledge-based inferences are provided to an information retrieval engine that retrieves a corresponding plurality of medical articles based on these knowledge-based inferences, and ranks each with respect to the knowledge-based inferences. A summary engine receives the ranked articles and creates a model based on the topical keywords and candidate sentences found in the highly ranked articles. A paraphrase engine processes the candidate sentences to provide a summary response based on a knowledge-based paraphrase model. An audio output device renders the summary report as the response to the user's original vocal query.Type: GrantFiled: September 25, 2017Date of Patent: January 3, 2023Assignee: Koninklijke Philips N.V.Inventors: Oladimeji Feyisetan Farri, Sheikh Al Hasan, Junyi Liu, Kathy Mi Young Lee, Vivek Varma Datla
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Patent number: 11544259Abstract: A method for determining, from a document, an answer to a query using a query answering system, comprising: (i) encoding, using an encoder, one or more documents; (ii) encoding a received query; (iii) generating, using an attention mechanism, a query-aware document representation comprising alignment between one or more words in one of the plurality of documents and one or more words in the query; (iv) generating, using a hierarchical self-attention mechanism, a word-to-sentence alignment of the query-aware document representation; (v) labeling, using a conditional random field classifier, each of a plurality of words in the word-to-sentence alignment with one of a one of a plurality of different sequence identifiers, resulting in possible labeled answering spans; and (vi) generating, from the one or more possible labeled answering spans, a response to the query.Type: GrantFiled: November 13, 2019Date of Patent: January 3, 2023Assignee: Koninklijke Philips N.V.Inventors: Sheikh Sadid Al Hasan, Tao Li, Vivek Varma Datla
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Patent number: 11449143Abstract: Methods and systems for generating text from a haptic-based input. The system may include an interface for receiving a haptic-based input and a processor executing instructions stored on a memory and providing a model. The model is configured to at least receive the haptic-based input and supply a text describing the haptic-based input using the interface.Type: GrantFiled: June 11, 2019Date of Patent: September 20, 2022Assignee: KONINKLIJKE PHILIPS N.V.Inventors: Oladimeji Feyisetan Farri, Junyi Liu, Sheikh Sadid Al Hasan, Vivek Varma Datla
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Publication number: 20220210376Abstract: A method of monitoring an event that is expected to progress along a planned event route includes receiving an indication of a current location of the event as the event progresses along the planned event route. Camera feeds that correspond to the current location of the event as the event progresses along the planned event route are automatically identified, selected and displayed on a situation awareness wall. Camera feeds that correspond to an expected future position of the event as the event progresses along the planned event route are automatically selected and displayed. Camera feeds that correspond to a previous position of the event as the event progresses along the planned event route are automatically removed from the situation awareness wall.Type: ApplicationFiled: December 30, 2020Publication date: June 30, 2022Inventors: Kondamari Raja Pratap, Shyamala Devi, Saravanan Kumar, Jayaraj Rajapandian, Vivek Varma Bharath, Anushka Srivastava, Deepak Sundar Meganathan, Pakkirisamy Suresh Kumar
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Publication number: 20220186952Abstract: An air cleaning apparatus includes a fan assembly configured to induce a vortex extending in front of the air cleaning apparatus for extracting air from a targeted region to remove and inactivate airborne pathogens (e.g., viruses) in the air. The air cleaning apparatus includes a reactor core configured to inactivate airborne pathogens via contact with anatase coated plates activated by UVC light. The air cleaning apparatus includes a filter assembly for removing reactive oxygen species in the decontaminated air.Type: ApplicationFiled: December 13, 2021Publication date: June 16, 2022Inventors: Vivek Varma, Vijaysimha Ajarananda
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Publication number: 20220108068Abstract: Techniques are described for training and/or utilizing sub-agent machine learning models to generate candidate dialog responses. In various implementations, a user-facing dialog agent (202, 302), or another component on its behalf, selects one of the candidate responses which is closest to user defined global priority objectives (318). Global priority objectives can include values (306) for a variety of dialog features such as emotion, confusion, objective-relatedness, personality, verbosity, etc. In various implementations, each machine learning model includes an encoder portion and a decoder portion. Each encoder portion and decoder portion can be a recurrent neural network (RNN) model, such as a RNN model that includes at least one memory layer, such as a long short-term memory (LSTM) layer.Type: ApplicationFiled: January 16, 2020Publication date: April 7, 2022Inventors: VIVEK VARMA DATLA, SHEIKH SADID AL HASAN, AADITYA PRAKASH, OLADIMEJI FEYISETAN FARRI, TILAK RAJ ARORA, JUNYI LIU, ASHEQUL QADIR
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Patent number: 11294942Abstract: Methods and systems for generating a question from free text. The system is trained on a corpus of data and receives a tuple consisting of a paragraph (free text), a focused fact, and a question type. The system implements a language model to find the most optimal combination of words to return a question for the paragraph about the focused fact.Type: GrantFiled: September 29, 2017Date of Patent: April 5, 2022Assignee: KONINKLIJK EPHILIPS N.V.Inventors: Reza Ghaeini, Sheikh Sadid Al Hasan, Oladimeji Feyisetan Farri, Kathy Mi Young Lee, Vivek Varma Datla, Ashequl Qadir, Junyi Liu, Adi Prakash
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Patent number: 11295861Abstract: Various embodiments described herein relate to a method, system, and non-transitory machine-readable medium including one or more of the following: extracting a first concept from input data presented for processing by a downstream function; identifying external data from an external resource based on the first concept; extracting a second concept from the external data; revising the first concept based on the second concept to produce a revised concept, wherein revising includes: applying a machine learning agent to determine whether to keep the first concept or adopt the second concept, and adopting the second concept in place of the first concept for use as the revised concept based on a decision by the machine learning agent to adopt the second concept; and further processing the revised concept according to the downstream function to generate an output.Type: GrantFiled: January 25, 2018Date of Patent: April 5, 2022Assignee: KONINKLIJKE PHILIPS N.V.Inventors: Sheikh Sadid Al Hasan, Yuan Ling, Oladimeji Feyisetan Farri, Vivek Varma Datla
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Patent number: 11232261Abstract: A system for automated question answering, comprising: a user interface configured to receive a query from a user; a question decomposition engine configured to decompose the query into one or more sub-questions and one or more contexts, and to align the sub-questions with contexts to generate question-context pairs; a query engine configured to query one or more answer resources with the question-context pairs to identify information likely to comprise an answer; and an answer generator configured to: (i) generate question-context-answer triples using the identified information from the query engine; (ii) select a generated question-context-answer triple comprising information most likely to comprise an answer to the identified sub-question; (iii) extract from the selected question-context-answer triple a portion of the associated information comprising an answer to the identified sub-question; and (iv) generate a natural language answer comprising a response to the query posed by the user.Type: GrantFiled: June 4, 2019Date of Patent: January 25, 2022Assignee: KONINKLIJKE PHILIPS N.V.Inventors: Vivek Varma Datla, Tilak Raj Arora, Junyi Liu, Sheikh Sadid Al Hasan, Oladimeji Feyisetan Farri
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Publication number: 20220020482Abstract: A non-transitory computer-readable medium stores instructions readable and executable by at least one electronic processor (20) to perform an augmented reality (AR) content generation method (100). The method includes: acquiring, with a camera (14) of an AR device (13), one or more images of a component of a medical imaging or medical therapy device (12); receiving, from a microphone (15) of the AR device, a triggering audio segment; generating one or more query data structures from both the one or more images and the triggering audio segment; retrieving AR instructional content related to the medical imaging or medical therapy device matching the generated one or more query data structures from a database (26); and outputting the AR instructional content one or more of (i) displayed superimposed on video displayed by the AR device and/or (ii) displayed on a head mounted display of the AR device and/or (iii) as audio content via a loudspeaker (27) of the AR device.Type: ApplicationFiled: December 2, 2019Publication date: January 20, 2022Inventors: Rithesh SREENIVASAN, Oladimeji Feyisetan FARRI, Sheikh Sadid AL HASAN, Tilak Raj ARORA, Vivek Varma DATLA
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Publication number: 20210357031Abstract: Methods and systems for generating text from a haptic-based input. The system may include an interface for receiving a haptic-based input and a processor executing instructions stored on a memory and providing a model. The model is configured to at least receive the haptic-based input and supply a text describing the haptic-based input using the interface.Type: ApplicationFiled: June 11, 2019Publication date: November 18, 2021Inventors: Oladimeji Feyisetan FARRI, Junyi LIU, Sheikh Sadid AL HASAN, Vivek Varma DATLA