BR112023013918A2 - METHOD AND SYSTEM FOR USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TO PROVIDE RECOMMENDATIONS TO A HEALTHCARE PROFESSIONAL IN REAL TIME DURING A TELEMEDICINE SESSION - Google Patents

METHOD AND SYSTEM FOR USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TO PROVIDE RECOMMENDATIONS TO A HEALTHCARE PROFESSIONAL IN REAL TIME DURING A TELEMEDICINE SESSION

Info

Publication number
BR112023013918A2
BR112023013918A2 BR112023013918A BR112023013918A BR112023013918A2 BR 112023013918 A2 BR112023013918 A2 BR 112023013918A2 BR 112023013918 A BR112023013918 A BR 112023013918A BR 112023013918 A BR112023013918 A BR 112023013918A BR 112023013918 A2 BR112023013918 A2 BR 112023013918A2
Authority
BR
Brazil
Prior art keywords
artificial intelligence
treatment
machine learning
real time
time during
Prior art date
Application number
BR112023013918A
Other languages
Portuguese (pt)
Inventor
Daniel Posnack
Jonathan Greene
Joseph Guaneri
Micheal Mueller
Peter Arn
Adam Hacking S
Steven Mason
Wendy Para
Original Assignee
Rom Tech Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US17/147,295 external-priority patent/US11087865B2/en
Priority claimed from US17/149,695 external-priority patent/US11282608B2/en
Application filed by Rom Tech Inc filed Critical Rom Tech Inc
Priority claimed from PCT/US2022/012187 external-priority patent/WO2022155251A1/en
Publication of BR112023013918A2 publication Critical patent/BR112023013918A2/en

Links

Landscapes

  • Computer And Data Communications (AREA)
  • Information Transfer Between Computers (AREA)
  • Machine Translation (AREA)

Abstract

método e sistema para uso de inteligência artificial e aprendizado por máquina para prover recomendações a um profissional de saúde em tempo real durante uma sessão de telemedicina. um método inclui receber dados de tratamento pertencentes a um usuário que usa um dispositivo de tratamento para realizar um plano de tratamento. o método também pode incluir gravar, em uma memória associada, configurada para ser acessada por um mecanismo de inteligência artificial, os dados de tratamento. o mecanismo de inteligência artificial pode ser configurado para usar pelo menos um modelo de aprendizado por máquina para gerar, usando os dados de tratamento, pelo menos um dentre uma previsão de saída de programação de tratamento e uma saída de consulta. o método também pode incluir receber, a partir do mecanismo de inteligência artificial, o pelo menos um dentre a previsão de saída de programação de tratamento e a saída de consulta. o método pode também modificar seletivamente, usando o pelo menos um dentre a previsão de saída de programação de tratamento e a saída de consulta, o pelo menos um aspecto do plano de tratamento.method and system for using artificial intelligence and machine learning to provide recommendations to a healthcare professional in real time during a telemedicine session. a method includes receiving treatment data belonging to a user who uses a treatment device to carry out a treatment plan. The method may also include recording, in an associated memory configured to be accessed by an artificial intelligence engine, the treatment data. The artificial intelligence engine may be configured to use at least one machine learning model to generate, using the treatment data, at least one of a treatment schedule output prediction and a query output. The method may also include receiving, from the artificial intelligence engine, the at least one of the predicted treatment schedule output and the query output. The method may also selectively modify, using the at least one of the treatment schedule output prediction and the query output, the at least one aspect of the treatment plan.

BR112023013918A 2021-01-12 2022-01-12 METHOD AND SYSTEM FOR USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TO PROVIDE RECOMMENDATIONS TO A HEALTHCARE PROFESSIONAL IN REAL TIME DURING A TELEMEDICINE SESSION BR112023013918A2 (en)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US17/147,295 US11087865B2 (en) 2019-10-03 2021-01-12 System and method for use of treatment device to reduce pain medication dependency
US17/149,695 US11282608B2 (en) 2019-10-03 2021-01-14 Method and system for using artificial intelligence and machine learning to provide recommendations to a healthcare provider in or near real-time during a telemedicine session
US17/397,385 US20210366587A1 (en) 2019-10-03 2021-08-09 System and method for use of treatment device to reduce pain medication dependency
US17/556,458 US20220115133A1 (en) 2019-10-03 2021-12-20 Method and system for using artificial intelligence and machine learning to provide recommendations to a healthcare provider in or near real-time during a telemedicine session
PCT/US2022/012187 WO2022155251A1 (en) 2021-01-12 2022-01-12 Method and system for using artificial intelligence and machine learning to provide recommendations to a healthcare provider in real-time during a telemedicine session

Publications (1)

Publication Number Publication Date
BR112023013918A2 true BR112023013918A2 (en) 2023-10-17

Family

ID=89028705

Family Applications (1)

Application Number Title Priority Date Filing Date
BR112023013918A BR112023013918A2 (en) 2021-01-12 2022-01-12 METHOD AND SYSTEM FOR USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TO PROVIDE RECOMMENDATIONS TO A HEALTHCARE PROFESSIONAL IN REAL TIME DURING A TELEMEDICINE SESSION

Country Status (1)

Country Link
BR (1) BR112023013918A2 (en)

Similar Documents

Publication Publication Date Title
US10418023B2 (en) Automatic answer rephrasing based on talking style
Clement et al. PyMT5: multi-mode translation of natural language and Python code with transformers
Rabovsky et al. Simulating the N400 ERP component as semantic network error: Insights from a feature-based connectionist attractor model of word meaning
MX2018011305A (en) Techniques for correcting linguistic training bias in training data.
Rosenbaum Motor programming: A review and scheduling theory
MacWhinney et al. Connectionism and language learning
CN111095259A (en) Natural language processing using N-GRAM machines
CN102043774A (en) Machine translation evaluation device and method
US9665566B2 (en) Computer-implemented systems and methods for measuring discourse coherence
Clarke Semantics and vocabulary
Li et al. Active learning for coreference resolution using discrete annotation
Chai et al. Learning to ask more: Semi-autoregressive sequential question generation under dual-graph interaction
Flickinger et al. The evolution of HPSG
BR112023013918A2 (en) METHOD AND SYSTEM FOR USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TO PROVIDE RECOMMENDATIONS TO A HEALTHCARE PROFESSIONAL IN REAL TIME DURING A TELEMEDICINE SESSION
Lau Neural indices of structured sentence representation: State of the art
Grambow et al. In-domain pre-training improves clinical note generation from doctor-patient conversations
Li et al. Understand the dynamic world: An end-to-end knowledge informed framework for open domain entity state tracking
Reddy et al. End-to-end QA on COVID-19: domain adaptation with synthetic training
GEP20237455B (en) Ai creation verification device
Pichai A retrieval-augmented generation based large language model benchmarked on a novel dataset
Wang et al. Ensemble-based fine-tuning strategy for temporal relation extraction from the clinical narrative
Pelowski et al. Chills, aesthetic experience, and new versus old knowledge-What do chills actually portend?: Comment on “Physics of mind: Experimental confirmations of theoretical predictions” by Schoeller et al
Zhao et al. Causal document-grounded dialogue pre-training
Besold Turing revisited: A cognitively-inspired decomposition
Moon et al. Effects of information masking in the task-specific Finetuning of a transformers-based clinical question-answering framework