# US 2021/0241872 A1 · Methods and systems for physiologically informed therapeutic provisions > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0241872 A1 - Document ID: US20210241872A1 - Status: Published application - Kind: A1 - Application number: 16/778,994 - Filed: 2020-01-31 - Published: 2021-08-05 - Earliest claimed: 2020-01-31 - Assignees: Kpn Innovations, LLC. - Applicants: KPN Innovations, LLC - Inventors: Kenneth Neumann - Web page: https://patentgrep.com/patent/US20210241872A1 ## CPC - G16H 20/00: ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance - G06N 20/00: Machine learning - G16H 10/60: for patient-specific data, e.g. for electronic patient records - G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients - G16H 20/17: delivered via infusion or injection - G16H 40/67: for remote operation - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients - G16H 70/20: relating to practices or guidelines - G16H 70/60: relating to pathologies - Y02A 90/10: Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - Y02A: TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE ## Abstract A system for physiologically informed therapeutic provisions includes a computing device configured to receive, from a remote device operated by a user, a conditional datum wherein the conditional datum contains a description of a current bodily complaint. The computing device is further configured to identify a plurality of antidotal therapeutic provisions, using a therapeutic clustering model wherein the therapeutic clustering model utilizes a conditional datum as an input and outputs antidotal therapeutic provisions. The computing device is further configured to locate a user biological extraction wherein the user biological extraction contains at least an element of user physiological data. The computing device is further configured to generate a compatibility model, wherein the compatibility model utilizes the antidotal therapeutic provisions and the user biological extraction as an input and outputs compatible antidotal therapeutic provisions. ## Claims ### Claim 1 A system for physiologically informed therapeutic provisions, the system comprising a computing device the computing device designed and configured to: receive, from a remote device operated by a user, a conditional datum, wherein the conditional datum contains a description of a current bodily complaint; identify a plurality of antidotal therapeutic provisions, using a therapeutic clustering model, wherein the therapeutic clustering model utilizes a conditional datum as an input and outputs antidotal therapeutic provisions; locate a first user biological extraction, wherein the first user biological extraction contains at least an element of user physiological data; and generate a compatibility model, wherein the compatibility model utilizes the antidotal therapeutic provisions and the first user biological extraction as an input and outputs compatible antidotal therapeutic provisions. ### Claim 2 (depends on 1) The system of claim 1, wherein the computing device is further configured to: retrieve a second user biological extraction; receive conditional training data, wherein conditional training data contains a plurality of biological extractions and a plurality of correlated conditions; and generate a conditional model, wherein the conditional model utilizes the second user biological extraction as an input and outputs a conditional datum containing a suspected condition. ### Claim 3 (depends on 1) The system of claim 1, wherein the computing device is further configured to receive from a remote device, operated by an informed advisor, the conditional datum containing a current bodily diagnosis. ### Claim 4 (depends on 1) The system of claim 1, wherein the computing device is further configured to identify the plurality of antidotal therapeutic provisions using the therapeutic clustering model by: receiving a clustering dataset, wherein the clustering dataset further comprises a plurality of unclassified cluster data entries; and calculating a first clustering algorithm. ### Claim 5 (depends on 4) The system of claim 4, wherein the first clustering algorithm further comprises a k-means clustering algorithm. ### Claim 6 (depends on 4) The system of claim 4, wherein the first clustering algorithm further comprises a hierarchical clustering algorithm. ### Claim 7 (depends on 1) The system of claim 1, wherein the computing device is further configured to: calculate a user effective age utilizing a user chronological age and a third user biological extraction; and analyze output antidotal therapeutic provisions as a function of the user effective age. ### Claim 8 (depends on 1) The system of claim 1, wherein the computing device is further configured to: input the conditional datum to a biological classifier, the biological classifier configured to input conditional datums and output related biological extractions by executing a classification algorithm; locate a fourth user biological extraction related to the conditional datum; and generate the compatibility model utilizing the fourth user biological extraction related to the conditional datum. ### Claim 9 (depends on 1) The system of claim 1, wherein the computing device is further configured to: receive compatibility training data, wherein compatibility training data further comprises a plurality of therapeutic provisions and biological extractions as inputs and outputs compatible antidotal therapeutic provisions; and calculate a compatibility model using a first machine-learning algorithm. ### Claim 10 (depends on 1) The system of claim 1, wherein the computing device is further configured to: retrieve a factor related to an antidotal therapeutic provision; generate the compatibility model as a function of the factor; and output compatible antidotal therapeutic provisions utilizing the factor. ### Claim 11 A method of physiologically informed therapeutic provisions, the method comprising: receiving, by a computing device, from a remote device operated by a user, a conditional datum, wherein the conditional datum contains a description of a current bodily complaint; identifying by the computing device, a plurality of antidotal therapeutic provisions, using a therapeutic clustering model, wherein the therapeutic clustering model utilizes a conditional datum as an input and outputs antidotal therapeutic provisions; locating by the computing device, a first user biological extraction, wherein the first user biological extraction contains at least an element of user physiological data; and generating by the computing device, a compatibility model wherein the compatibility model utilizes the antidotal therapeutic provisions and the first user biological extraction as an input and outputs compatible antidotal therapeutic provisions. ### Claim 12 (depends on 11) The method of claim 11, wherein receiving the conditional datum further comprises: retrieving a second user biological extraction; receiving, conditional training data, wherein conditional training data contains a plurality of biological extractions and a plurality of correlated conditions; and generating a conditional model, wherein the conditional model utilizes the second user biological extraction as an input and outputs a conditional datum containing a suspected condition. ### Claim 13 (depends on 11) The method of claim 11, wherein receiving the conditional datum further comprises receiving from a remote device, operated by an informed advisor, a conditional datum containing a current bodily diagnosis. ### Claim 14 (depends on 11) The method of claim 11, wherein identifying the plurality of antidotal therapeutic provisions further comprises: receiving a clustering dataset, wherein the clustering dataset further comprises a plurality of unclassified cluster data entries; and calculating a first clustering algorithm. ### Claim 15 (depends on 14) The method of claim 14, wherein calculating the first clustering algorithm further comprises calculating a k-means clustering algorithm. ### Claim 16 (depends on 14) The method of claim 14, wherein calculating the first clustering algorithm further comprises calculating a hierarchical clustering algorithm. ### Claim 17 (depends on 11) The method of claim 11, wherein identifying the plurality of antidotal therapeutic provisions further comprises: calculating a user effective age utilizing a user chronological age and a third user biological extraction; and analyzing output antidotal therapeutic provisions as a function of the user effective age. ### Claim 18 (depends on 11) The method of claim 11, wherein locating the biological extraction further comprises: inputting the conditional datum to a biological classifier, the biological classifier configured to input conditional datums and output related biological extractions by executing a classification algorithm; locating a fourth user biological extraction related to the conditional datum; and generating the compatibility model utilizing the fourth user biological extraction related to the conditional datum. ### Claim 19 (depends on 11) The method of claim 11, wherein generating the compatibility model further comprises: receiving compatibility training data, wherein compatibility training data further comprises a plurality of therapeutic provisions and biological extractions as inputs and outputs compatible antidotal therapeutic provisions; and calculating a compatibility model using a first machine-learning algorithm. ### Claim 20 (depends on 11) The method of claim 11 further comprising: retrieving a factor related to an antidotal therapeutic provision; generating the compatibility model as a function of the factor; and outputting compatible antidotal therapeutic provisions utilizing the factor.