Diagnosis and treatment recommendation using quantum computing

US12548675B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-12548675-B2
Application numberUS-202117646252-A
CountryUS
Kind codeB2
Filing dateDec 28, 2021
Priority dateDec 28, 2021
Publication dateFeb 10, 2026
Grant dateFeb 10, 2026

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Abstract

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This disclosure describes techniques for providing diagnosis and treatment recommendations using quantum computing. For example, a quantum computing device encodes diagnosis-relevant information of a patient as one or more patient diagnosis qubits. The quantum computing device implements a first quantum search algorithm using the patient diagnosis qubits to determine a diagnosis likelihood for each condition of a plurality of conditions. The quantum computing device further encodes the diagnosis data and treatment-relevant information of the patient as one or more patient treatment qubits. The quantum computing device implements a second quantum search algorithm using the treatment-relevant information of the patient to determine one or more treatment recommendations for the patient.

First claim

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What is claimed is: 1 . A quantum computing device comprising: a first quantum encoder configured to encode diagnosis-relevant information associated with a patient as one or more patient diagnosis qubits; a first quantum circuit configured as a first quantum search algorithm to: receive as input the one or more patient diagnosis qubits and a plurality of diagnosis probability qubits each encoded with a respective diagnosis probability for a corresponding condition of a plurality of conditions, and output at least a first diagnosis probability qubit of the plurality of diagnosis probability qubits that matches a state of one of the one or more patient diagnosis qubits, the first diagnosis probability qubit encoding a diagnosis probability associated with a first condition from among the plurality of conditions; a second quantum encoder configured to encode diagnosis data and treatment-relevant information as one or more patient treatment qubits, wherein the diagnosis data comprises at least the diagnosis probability and the first condition; and a second quantum circuit configured as a second quantum search algorithm to: receive as input the one or more patient treatment qubits and a plurality of risk or efficacy qubits each encoded with at least one of a respective risk or respective efficacy of a corresponding treatment of a plurality of treatments, and output a first risk or efficacy qubit of the plurality of risk or efficacy qubits that matches a state of one of the one or more patient treatment qubits, the first risk or efficacy qubit being encoded with at least one of a risk or efficacy of a particular treatment of the plurality of treatments for treating the first condition, wherein the quantum computing device is configured to decode the first risk or efficacy qubit into classical data specifying the particular treatment and output the classical data to a classical computing device configured to output the classical data for display on the classical computing device. 2 . The quantum computing device of claim 1 , wherein the diagnosis-relevant information associated with the patient comprises at least one of one or more characteristics of the patient, one or more symptoms of the patient, or a medical history of the patient. 3 . The quantum computing device of claim 1 , wherein the treatment-relevant information comprises one or more of medication adherence information of the patient or medication efficacy information of the patient. 4 . The quantum computing device of claim 1 , wherein the diagnosis probability for each condition of the plurality of conditions is computed based on the diagnosis-relevant information associated with the patient. 5 . The quantum computing device of claim 1 , wherein the first quantum search algorithm and the second quantum search algorithm are based at least in part on Grover's algorithm. 6 . The quantum computing device of claim 1 , wherein the particular treatment is associated with a recommendation score computed based on at least one of a risk of a particular drug in treating a particular condition of the plurality of conditions, an efficacy of the particular drug in treating the particular condition, a risk associated with using the particular drug incorrectly, a likelihood of the patient having the particular condition, or a likelihood of the patient using the particular drug incorrectly. 7 . A computer-implemented method comprising: encoding, by a quantum computing device, diagnosis-relevant information associated with a patient as one or more patient diagnosis qubits; receiving, by a first quantum circuit configured as a first quantum search algorithm of the quantum computing device, as input the one or more patient diagnosis qubits and a plurality of diagnosis probability qubits each encoded with a respective diagnosis probability for a corresponding condition of a plurality of conditions, and outputting, by the first quantum circuit, at least a first diagnosis probability qubit of the plurality of diagnosis probability qubits that matches a state of one of the one or more patient diagnosis qubits, the first diagnosis probability qubit encoding a diagnosis probability associated with a first condition from among the plurality of conditions; encoding, by the quantum computing device, diagnosis data and treatment-relevant information as one or more patient treatment qubits, wherein the diagnosis data comprises at least the diagnosis probability and the first condition; receiving, by a second quantum circuit configured as a second quantum search algorithm of the quantum computing device, as input the one or more patient treatment qubits and a plurality of risk or efficacy qubits each encoded with at least one of respective risk or respective efficacy of a corresponding treatment of a plurality of treatments, outputting, by the second quantum circuit, a first risk or efficacy qubit of the plurality of risk or efficacy qubits that matches a state of one of the one or more patient treatment qubits, the first risk or efficacy qubit being encoded with at least one of a risk or efficacy of a particular treatment of the plurality of treatments for treating the first condition; decoding, by the quantum computing device, the first risk or efficacy qubit into classical data specifying the particular treatment; and outputting, by the quantum computing device, the classical data to a classical computing device configured to output the classical data for display on the classical computing device. 8 . The computer-implemented method of claim 7 , wherein the diagnosis-relevant information associated with the patient comprises at least one of one or more characteristics of the patient, one or more symptoms of the patient, or medical history of the patient. 9 . The computer-implemented method of claim 7 , wherein the treatment-relevant information comprises one or more of medication adherence information of the patient or medication efficacy information of the patient. 10 . The computer-implemented method of claim 7 , wherein the diagnosis probability for each condition of the plurality of conditions is computed based on the diagnosis-relevant information associated with the patient. 11 . The computer-implemented method of claim 7 , wherein the first quantum search algorithm is based at least in part on Grover's algorithm. 12 . The computer-implemented method of claim 7 , further comprising: computing, by the quantum computing device, a recommendation score for the particular treatment, wherein the recommendation score is computed based on at least one of a risk of a particular drug in treating a particular condition of the plurality of conditions, an efficacy of the particular drug in treating the particular condition, a risk associated with using the particular drug incorrectly, a likelihood of the patient having the particular condition, or a likelihood of the patient using the particular drug incorrectly. 13 . One or more non-transitory computer-readable storage media encoded with processor-executable instructions that, when executed by one or more processors, cause the one or more processors to: encode diagnosis-relevant information associated with a patient as one or more patient diagnosis qubits; receive as input one or more patient diagnosis qubits and a plurality of diagnosis probability qubits each encoded with a respective diagnosis probability for a corresponding condition of a plurality of conditions; output at least a first diagnosis probability qubit of the plurality of diagnosis probability qubits that matches a state of one of the one or more patient diagnosis qubits, the firs

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Classifications

  • Physical realisations or architectures of quantum processors or components for manipulating qubits, e.g. qubit coupling or qubit control · CPC title

  • Quantum algorithms, e.g. based on quantum optimisation, quantum Fourier or Hadamard transforms · CPC title

  • Models of quantum computing, e.g. quantum circuits or universal quantum computers · CPC title

  • G16H50/20Primary

    for computer-aided diagnosis, e.g. based on medical expert systems · CPC title

  • relating to drugs, e.g. their side effects or intended usage · CPC title

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What does patent US12548675B2 cover?
This disclosure describes techniques for providing diagnosis and treatment recommendations using quantum computing. For example, a quantum computing device encodes diagnosis-relevant information of a patient as one or more patient diagnosis qubits. The quantum computing device implements a first quantum search algorithm using the patient diagnosis qubits to determine a diagnosis likelihood for …
Who is the assignee on this patent?
Optum Services Ireland Ltd
What technology area does this patent fall under?
Primary CPC classification G16H50/20. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Feb 10 2026 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 9 related publications on this page (citations in our corpus or others sharing the same primary CPC).