# US 2020/0401904 A1 · Adaptive medical imaging device configuration using artificial intelligence > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401904 A1 - Document ID: US20200401904A1 - Status: Published application - Kind: A1 - Application number: 16/450,480 - Filed: 2019-06-24 - Published: 2020-12-24 - Earliest claimed: 2019-06-24 - Assignees: GE Precision Healthcare LLC - Applicants: GE Precision Healthcare LLC - Inventors: Anurag Voleti; Sridhar Nuthi - Web page: https://patentgrep.com/patent/US20200401904A1 ## CPC - G06N 3/126: Evolutionary algorithms, e.g. genetic algorithms or genetic programming - G06N 3/086: using evolutionary algorithms, e.g. genetic algorithms or genetic programming - G06N 20/00: Machine learning - A61B 8/58: {Testing, adjusting or calibrating the diagnostic device} - G06N 3/02: Neural networks - G16H 40/40: for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract Methods, apparatus, systems and articles of manufacture to provide a mutatable machine genetic structure are disclosed. An example apparatus includes memory including instructions for execution by a processor and a machine genetic structure specifying composition, performance, and health of a machine; and at least one processor. The processor is to execute the instructions to at least: evaluate the machine genetic structure with respect to an operating condition of the machine to identify a discrepancy and/or an opportunity for improvement for the machine genetic structure to satisfy the operating condition; determine a mutation of the machine genetic structure from a first sequence to a second sequence to address the discrepancy and/or opportunity for improvement to satisfy the operating condition; and set the machine genetic structure from the first sequence to the mutation of the second sequence to configure the machine for operation according to the machine genetic structure. ## Claims ### Claim 1 An apparatus comprising: memory including instructions for execution by at least one processor and a machine genetic structure specifying composition, performance, and health of a machine; and at least one processor to execute the instructions to at least: evaluate the machine genetic structure with respect to an operating condition of the machine to identify at least one of a discrepancy or an opportunity for improvement for the machine genetic structure to satisfy the operating condition; determine a mutation of the machine genetic structure from a first sequence to a second sequence to address the at least one of a discrepancy or an opportunity for improvement to satisfy the operating condition; and set the machine genetic structure from the first sequence to the mutation of the second sequence to configure the machine for operation according to the machine genetic structure. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein the at least one processor includes: a gene analyzer to analyze the machine genetic structure; a gene modifier to mutate the machine genetic structure; and a gene communicator to transmit the machine genetic structure. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein the operating condition includes at least one of a) a task to be executed by the machine or b) a parameter to configure the machine. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein the discrepancy indicates an error at the machine. ### Claim 5 (depends on 1) The apparatus of claim 1, wherein the at least one processor is to store the mutation to transmit to a second machine. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein the at least one processor is to evaluate the machine genetic structure with respect to an operating condition of the machine to identify at least one of a discrepancy or an opportunity for improvement for the machine genetic structure to satisfy the operating condition by comparing the machine genetic structurer to at least one of a) a set of stored machine genetic structures or b) a plurality of machine genetic structures associated with a fleet including the machine and a plurality of additional machines. ### Claim 7 (depends on 1) The apparatus of claim 1, wherein the machine genetic structure is formed as a function of hardware, software, and operating conditions of the machine leveraging additional machine genetic structures from a cloud-based system via an edge device to configure the machine. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein the machine genetic structure includes a data structure to alter the configuration of the machine, specify the performance of the machine with respect to the operating condition, and establish a boundary for the health of the machine in operating with respect to the operating condition. ### Claim 9 A non-transitory computer readable storage medium comprising instructions which, when executed, cause a machine to at least: evaluate a machine genetic structure with respect to an operating condition of the machine to identify at least one of a discrepancy or an opportunity for improvement for the machine genetic structure to satisfy the operating condition, the machine genetic structure specifying composition, performance, and health of the machine; determine a mutation of the machine genetic structure from a first sequence to a second sequence to address the at least one of a discrepancy or an opportunity for improvement to satisfy the operating condition; and set the machine genetic structure from the first sequence to the mutation of the second sequence to configure the machine for operation according to the machine genetic structure. ### Claim 10 (depends on 9) The non-transitory computer readable storage medium of claim 9, wherein the operating condition includes at least one of a) a task to be executed by the machine or b) a parameter to configure the machine. ### Claim 11 (depends on 9) The non-transitory computer readable storage medium of claim 9, wherein the discrepancy indicates an error at the machine. ### Claim 12 (depends on 9) The non-transitory computer readable storage medium of claim 9, wherein the instructions, when executed, cause the machine to store the mutation to transmit to a second machine. ### Claim 13 (depends on 9) The non-transitory computer readable storage medium of claim 9, wherein the instructions, when executed, cause the machine to evaluate the machine genetic structure with respect to an operating condition of the machine to identify at least one of a discrepancy or an opportunity for improvement for the machine genetic structure to satisfy the operating condition by comparing the machine genetic structurer to at least one of a) a set of stored machine genetic structures or b) a plurality of machine genetic structures associated with a fleet including the machine and a plurality of additional machines. ### Claim 14 (depends on 9) The non-transitory computer readable storage medium of claim 9, wherein the machine genetic structure is formed as a function of hardware, software, and operating conditions of the machine leveraging additional machine genetic structures from a cloud-based system via an edge device to configure the machine. ### Claim 15 A method comprising: evaluating, by executing an instruction using at least one processor, a machine genetic structure with respect to an operating condition of the machine to identify at least one of a discrepancy or an opportunity for improvement for the machine genetic structure to satisfy the operating condition, the machine genetic structure specifying composition, performance, and health of the machine; determining, by executing an instruction using the at least one processor, a mutation of the machine genetic structure from a first sequence to a second sequence to address the at least one of a discrepancy or an opportunity for improvement to satisfy the operating condition; and setting, by executing an instruction using the at least one processor, the machine genetic structure from the first sequence to the mutation of the second sequence to configure the machine for operation according to the machine genetic structure. ### Claim 16 (depends on 15) The method of claim 15, wherein the operating condition includes at least one of a) a task to be executed by the machine or b) a parameter to configure the machine. ### Claim 17 (depends on 15) The method of claim 15, wherein the discrepancy indicates an error at the machine. ### Claim 18 (depends on 15) The method of claim 15, further including storing the mutation to transmit to a second machine. ### Claim 19 (depends on 15) The method of claim 15, wherein evaluating the machine genetic structure with respect to an operating condition of the machine to identify at least one of a discrepancy or an opportunity for improvement for the machine genetic structure to satisfy the operating condition further includes comparing the machine genetic structurer to at least one of a) a set of stored machine genetic structures or b) a plurality of machine genetic structures associated with a fleet including the machine and a plurality of additional machines. ### Claim 20 (depends on 15) The method of claim 15, wherein the machine genetic structure is formed as a function of hardware, software, and operating conditions of the machine leveraging additional machine genetic structures from a cloud-based system via an edge device to configure the machine.