公开(公告)号：US20240363211A1

公开(公告)日：2024-10-31

申请号：US18641300

申请日：2024-04-19

申请人： BULL SAS

发明人： Mitesh Vikram KOTHARI

IPC分类号： G16H15/00 ,  G16H10/20 ,  G16H10/60 ,  G16H20/00 ,  G16H40/20 ,  G16H50/30 ,  G16H50/70

CPC分类号： G16H15/00 ,  G16H10/20 ,  G16H10/60 ,  G16H20/00 ,  G16H40/20 ,  G16H50/30 ,  G16H50/70

摘要： The invention relates to a method for determining a future health condition of an individual. The method including providing health data of the individual, obtaining a health condition information from the health data of the individual, encoding the health data and the health condition information of the individual in a low-dimensional vector that includes the health data and the health condition information of the individual, obtaining a trained neural network taking as input a low-dimensional vector of the individual and configured to determine a future health condition of the individual, and determining a future health condition of the individual by inputting the health condition information of the individual to the trained neural network. The invention also relates to a system configured to carry out the method.

公开(公告)号：US12127794B2

公开(公告)日：2024-10-29

申请号：US17597042

申请日：2020-06-25

申请人： Quantum Surgical

发明人： Estanislao Oubel ,  Lucien Blondel ,  Fernand Badano ,  Bertin Nahum

IPC分类号： A61B18/00 ,  A61B18/02 ,  A61B18/04 ,  A61B18/18 ,  A61B18/20 ,  A61B34/10 ,  G06N3/045 ,  G06N3/08 ,  G16H20/40 ,  G16H30/40 ,  G16H50/50 ,  G16H50/70

CPC分类号： A61B34/10 ,  A61B18/02 ,  A61B18/04 ,  A61B18/1815 ,  A61B18/20 ,  G06N3/045 ,  G06N3/08 ,  G16H20/40 ,  G16H30/40 ,  G16H50/50 ,  G16H50/70 ,  A61B2018/00577 ,  A61B2034/104 ,  A61B2034/105 ,  A61B2034/107 ,  A61B2034/108

摘要： The invention relates to a method and device for planning a surgical procedure aiming to ablate a tissue in an anatomical area of interest of a patient. On the basis of a preoperative image of the anatomical area of interest and of a set of planning parameters (P), a simulated image is generated by a neural network that has been previously trained using learning elements corresponding, respectively, to a similar surgical procedure for ablating a tissue in an anatomical area of interest for another patient. Each learning element comprises a preoperative image of the anatomical area of interest of a patient, planning parameters (P) used for the surgical procedure on this patient, and a postoperative image of the anatomical area of interest of this patient after the surgical procedure. An estimated ablation region may be segmented in the simulated image in order to be compared with a segmented region to be treated in the preoperative image.

公开(公告)号：US12127793B2

公开(公告)日：2024-10-29

申请号：US17428193

申请日：2020-02-04

申请人： Smith & Nephew, Inc. ,  Smith & Nephew Asia Pacific Pte. Limited ,  Smith & Nephew Orthopaedics AG

发明人： Shawn P. McGuan ,  Elizabeth Duxbury

IPC分类号： A61B34/10 ,  A61B17/17 ,  A61B34/00 ,  A61B90/00 ,  A61F2/46 ,  G02B27/01 ,  G06N3/08 ,  G06N5/046 ,  G06N20/00 ,  G06N20/10 ,  G09B5/02 ,  G09B19/00 ,  G09B19/24 ,  G16H10/60 ,  G16H20/40 ,  G16H30/40 ,  G16H40/63 ,  G16H50/50 ,  G16H50/70 ,  A61B17/00 ,  A61B17/15 ,  A61B34/20 ,  A61B34/30 ,  A61B90/50 ,  A61B90/96 ,  A61F2/30

CPC分类号： A61B34/10 ,  A61B17/1764 ,  A61B34/25 ,  A61B90/361 ,  A61B90/37 ,  A61B90/39 ,  A61F2/461 ,  G02B27/0172 ,  G06N3/08 ,  G06N5/046 ,  G06N20/00 ,  G06N20/10 ,  G09B5/02 ,  G09B19/003 ,  G09B19/24 ,  G16H10/60 ,  G16H20/40 ,  G16H30/40 ,  G16H40/63 ,  G16H50/50 ,  G16H50/70 ,  A61B2017/00199 ,  A61B2017/00526 ,  A61B17/15 ,  A61B17/17 ,  A61B2034/102 ,  A61B2034/104 ,  A61B2034/105 ,  A61B2034/107 ,  A61B2034/108 ,  A61B34/20 ,  A61B2034/2048 ,  A61B2034/2057 ,  A61B2034/2063 ,  A61B2034/2065 ,  A61B2034/2068 ,  A61B2034/2072 ,  A61B2034/2074 ,  A61B2034/252 ,  A61B2034/254 ,  A61B2034/256 ,  A61B2034/258 ,  A61B34/30 ,  A61B2090/363 ,  A61B2090/365 ,  A61B2090/371 ,  A61B2090/376 ,  A61B2090/3916 ,  A61B2090/502 ,  A61B90/96 ,  A61F2002/30952 ,  A61F2002/4633 ,  G02B2027/0138

摘要： A method and system for performing hip arthroplasty include analyzing images of a patient's hip joint in a plurality of positions to identify preoperative hip geometry. A statistical patient model predicts prosthetic hip implant performance based on the preoperative knee geometry and given prosthetic knee implant implantation parameters for a plurality of selected patient activities, each having a predefined motion profile to calculate an optimized surgical plan for performing the procedure using a computer assisted surgical system, which may use fiducial markers affixed to patient tissue. Hip geometry can be determined by angles between landmarks in the images, including sacral tilt, pelvic incidence, pelvic femoral angle, and ante-inclination angle in x-ray images. Implant performance criteria can include, for example, edge loading and range of motion of implant components.

公开(公告)号：US20240355471A1

公开(公告)日：2024-10-24

申请号：US18525115

申请日：2023-11-30

申请人： SOAP, Inc.

发明人： Steven Charlap

IPC分类号： G16H50/20 ,  G16H10/20 ,  G16H20/10 ,  G16H40/67 ,  G16H50/30 ,  G16H50/70

CPC分类号： G16H50/20 ,  G16H10/20 ,  G16H20/10 ,  G16H40/67 ,  G16H50/30 ,  G16H50/70

摘要： Leveraging generative artificial intelligence to provide diagnoses for patients. In some examples, elimination rules based on patient intake data are applied to a very large corpus of candidate diagnoses, such as all known human medical diagnoses, to narrow down the very large corpus of candidates to a meaningful differential diagnosis or final diagnosis. In some examples, targeted information is elicited to determine and apply additional elimination rules to further narrow down the candidate diagnoses. In some examples, patient intake data is classified into risk data and symptom data and processed by data type-specific machine learning models. In some examples, patient intake data is reconciled and correlated between risk and symptom data by specific machine-learning models to improve diagnostic clustering and accuracy.

公开(公告)号：US12119115B2

公开(公告)日：2024-10-15

申请号：US18156010

申请日：2023-01-18

申请人： Evidation Health, Inc.

发明人： Luca Foschini ,  Filip Jankovic ,  Raghunandan Melkote Kainkaryam ,  Juan Ignacio Oguiza Mendez ,  Arinbjörn Kolbeinsson

IPC分类号： G16H50/20 ,  G16H50/70

CPC分类号： G16H50/20 ,  G16H50/70

摘要： Disclosed is a method comprising accessing, by a machine learning system, a set of data records for a plurality of users, the data records representative of physical statistics measured for each of the plurality of users over a time period. At least a subset of the data records comprises patterns of missing data for at least a portion of the time period. The method also comprises generating a set of masked data records by masking a subset of the data records in accordance with a pattern of natural missingness from a data record. The method also comprises generating, by the machine learning system, a set of learned representations from at least the set of masked data records. Finally, the method comprises fine tuning, by the machine learning system, a machine learning model using the set of learned representations, the machine learning model configured to perform a downstream machine learning task.

公开(公告)号：US20240337580A1

公开(公告)日：2024-10-10

申请号：US18291790

申请日：2022-07-26

申请人： Hoffmann-La Roche Inc.

发明人： Priscila CAMILLO TEIXEIRA ,  José Manuel MARTINS ABRANTES TEIXEIRA DUARTE ,  Raul RODRIGUEZ-ESTEBAN ,  WeiQing Venus SO

IPC分类号： G01N15/1429 ,  G16B40/00 ,  G16H50/70

CPC分类号： G01N15/1429 ,  G16B40/00 ,  G16H50/70

摘要： A system for determining a cell type and/or one or more functional markers of a cell using flow cytometry. A plurality of flow cytometry devices respectively perform flow cytometry of cells and use gating definitions at least in part different among each other, thereby generating gating definitions as respective results of the flow cytometry devices, which are at least partly inconsistent such that a same set of biomarkers detected by two different flow cytometry devices results in different gating definitions being output. A machine learning component receives the gating definitions as inputs, and generates a set of cell types and/or functional markers as an output and as a result of the flow cytometry analysis performed by the flow cytometry devices. The machine learning component has been trained using a set of manually curated training data comprising gating definitions resulting from the flow cytometry and corresponding cell types and/or functional markers.

公开(公告)号：US12112843B2

公开(公告)日：2024-10-08

申请号：US17117654

申请日：2020-12-10

申请人： HOWMEDICA OSTEONICS CORP.

发明人： Sergii Poltaretskyi ,  Jean Chaoui ,  Damien Cariou

IPC分类号： G16H20/40 ,  A61B5/00 ,  A61B5/11 ,  A61B17/14 ,  A61B17/16 ,  A61B17/17 ,  A61B34/00 ,  A61B34/10 ,  A61B90/00 ,  A61B90/92 ,  A61F2/40 ,  G02B27/00 ,  G02B27/01 ,  G06F3/01 ,  G06F3/04815 ,  G06F3/0482 ,  G06F30/10 ,  G06F30/20 ,  G06N3/08 ,  G06N20/00 ,  G06T7/00 ,  G06T7/11 ,  G06T7/55 ,  G06T11/00 ,  G06T19/00 ,  G06T19/20 ,  G09B5/06 ,  G09B9/00 ,  G09B19/00 ,  G09B23/28 ,  G16H30/20 ,  G16H30/40 ,  G16H40/20 ,  G16H40/60 ,  G16H40/63 ,  G16H40/67 ,  G16H50/30 ,  G16H50/50 ,  G16H50/70 ,  G16H70/20 ,  G16H70/60 ,  G16H80/00 ,  H04N13/122 ,  H04N13/332 ,  A61B17/00 ,  A61B17/15 ,  A61B34/20 ,  A61B90/50 ,  A61F2/46 ,  G06F3/0483 ,  G06N3/04 ,  G16H50/20

CPC分类号： G16H20/40 ,  A61B5/1114 ,  A61B5/1121 ,  A61B5/1127 ,  A61B5/681 ,  A61B17/142 ,  A61B17/1604 ,  A61B17/1626 ,  A61B17/1659 ,  A61B17/1684 ,  A61B17/1703 ,  A61B34/10 ,  A61B34/25 ,  A61B90/08 ,  A61B90/36 ,  A61B90/361 ,  A61B90/37 ,  A61B90/39 ,  A61B90/92 ,  A61F2/40 ,  A61F2/4081 ,  G02B27/0075 ,  G02B27/017 ,  G02B27/0172 ,  G06F3/011 ,  G06F3/04815 ,  G06F3/0482 ,  G06F30/10 ,  G06F30/20 ,  G06N3/08 ,  G06N20/00 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/55 ,  G06T11/00 ,  G06T19/006 ,  G06T19/20 ,  G09B5/06 ,  G09B9/00 ,  G09B19/003 ,  G09B23/28 ,  G16H30/20 ,  G16H30/40 ,  G16H40/20 ,  G16H40/60 ,  G16H40/63 ,  G16H40/67 ,  G16H50/30 ,  G16H50/50 ,  G16H50/70 ,  G16H70/20 ,  G16H70/60 ,  G16H80/00 ,  H04N13/122 ,  H04N13/332 ,  A61B5/744 ,  A61B2017/00115 ,  A61B2017/00119 ,  A61B2017/00123 ,  A61B17/151 ,  A61B17/1775 ,  A61B17/1778 ,  A61B2034/102 ,  A61B2034/104 ,  A61B2034/105 ,  A61B2034/107 ,  A61B2034/108 ,  A61B2034/2048 ,  A61B2034/2051 ,  A61B2034/2055 ,  A61B2034/2065 ,  A61B2034/2068 ,  A61B2034/252 ,  A61B2034/254 ,  A61B2090/062 ,  A61B2090/067 ,  A61B2090/0801 ,  A61B2090/0807 ,  A61B2090/365 ,  A61B2090/366 ,  A61B2090/367 ,  A61B2090/368 ,  A61B2090/373 ,  A61B2090/374 ,  A61B2090/3762 ,  A61B2090/378 ,  A61B2090/3937 ,  A61B2090/3945 ,  A61B2090/397 ,  A61B2090/502 ,  A61B2505/05 ,  A61B2562/0219 ,  A61F2002/4011 ,  A61F2/4606 ,  A61F2/4612 ,  A61F2002/4633 ,  A61F2002/4658 ,  A61F2002/4668 ,  G02B2027/0141 ,  G02B2027/0174 ,  G06F3/0483 ,  G06N3/04 ,  G06T2200/24 ,  G06T2207/10016 ,  G06T2207/20036 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30008 ,  G06T2207/30052 ,  G06T2207/30204 ,  G06T2210/41 ,  G06T2219/2004 ,  G06V2201/03 ,  G16H50/20

摘要： An example system for demonstrating at least one aspect of an orthopedic surgical procedure includes a first device configured to display a presentation to a first user while the first user is wearing the device, wherein the presentation includes virtual element(s) that are controllable by the first user while the first user is wearing the first device, and wherein the virtual element(s) comprise a 3-dimensional (3D) virtual representation of one or more anatomical features associated with the orthopedic surgical procedure; and a second device configured to display the presentation to a second user, wherein the virtual element(s) further include virtual pre-operative plan element(s) shown relative to the 3D virtual representation, virtual surgical guidance feature(s) shown relative to the 3D virtual representation, or surgical result(s) virtually illustrated on the 3D virtual representation so as to demonstrate aspect(s) of the orthopedic surgical procedure.

公开(公告)号：US12109024B2

公开(公告)日：2024-10-08

申请号：US17045272

申请日：2019-04-05

申请人： LIFE METER SRL

发明人： Fernando De Benedetto ,  Alberto Visconti ,  Marco Raimondi ,  Matteo Aventaggiato

IPC分类号： A61B5/00 ,  A61B5/0205 ,  A61B5/1455 ,  A61B5/1495 ,  G16H10/60 ,  G16H40/40 ,  G16H40/67 ,  G16H50/30 ,  G16H50/70 ,  A61B5/024

CPC分类号： A61B5/1495 ,  A61B5/0205 ,  A61B5/14552 ,  A61B5/6802 ,  A61B5/6833 ,  G16H10/60 ,  G16H40/40 ,  G16H40/67 ,  G16H50/30 ,  G16H50/70 ,  A61B5/02433 ,  A61B2560/0214 ,  A61B2560/0238 ,  A61B2560/0456

摘要： A method of measuring blood oxygenation consists of measuring Sp02 on one or more test subjects using a first, reference pulse oximetry device (100), such as a medical- grade pulse-oximeter of the kind that employs, for example, a finger-tip clip-type probe. This can be done on each patient over relatively short time periods. Then, the Sp02 is monitored on a target subject across a relatively longer time period using a second, wearable pulse oximetry device (10) that can be worn non-intrusively by the target use, for example in the form of a bracelet. The Sp02 measured using the wearable pulse oximetry device (10), can be measured based on calibration measurements performed using the first, reference pulse oximetry device (100). In this way, the measurements produced by the wearable pulse oximetry device (10) are calibrated using a medical-grade pulse- oximeter (100).

公开(公告)号：US20240331825A1

公开(公告)日：2024-10-03

申请号：US18576394

申请日：2022-06-27

申请人： KONINKLIJKE PHILIPS N.V.

发明人： ERAN SIMHON ,  LASITH ADHIKARI ,  DAVID PAUL NOREN ,  GREGORY BOVERMAN ,  CHAITANYA KULKARNI ,  SYAMANTHAKA BALAKRISHNAN ,  VIKRAM SHIVANNA ,  LARRY JAMES ESHELMAN

IPC分类号： G16H20/00 ,  G16H50/70

CPC分类号： G16H20/00 ,  G16H50/70

摘要： Generally, in one aspect a process for providing adaptive suggestions in the CPOE is provided. The process includes: (i) generating a rule set from historic patient data (ii) receiving data specific to a patient (iii) determining, by a processor of the adaptive suggestion system containing a set of created rules, the most likely entry for that component of the CPOE based on the rule set and received patient data (iv) displaying via user interface the suggested entry for the component of the CPOE.

公开(公告)号：US20240325085A1

公开(公告)日：2024-10-03

申请号：US18739125

申请日：2024-06-10

申请人： Medicrea International

发明人： David Ryan ,  Denys Sournac ,  Thomas Mosnier ,  Christophe X. Javelot ,  Agathe Senac ,  Céline Augagneur

IPC分类号： A61B34/10 ,  A61B17/70 ,  A61B34/00 ,  A61B34/20 ,  A61B90/00 ,  A61F2/46 ,  G16H50/50 ,  G16H50/70

CPC分类号： A61B34/10 ,  A61B17/7002 ,  A61B34/20 ,  G16H50/50 ,  G16H50/70 ,  A61B17/7001 ,  A61B17/7074 ,  A61B2034/101 ,  A61B2034/104 ,  A61B2034/108 ,  A61B2034/2048 ,  A61B34/25 ,  A61B2034/252 ,  A61B2034/256 ,  A61B2090/376 ,  A61B2090/3762 ,  A61F2/4657

摘要： The disclosure herein relate to systems, methods, and devices for developing patient-specific spinal treatments, operations, and procedures. In some embodiments, systems, methods, and devices described herein for developing patient-specific spinal treatments, operations, and procedures can comprise an iterative virtuous cycle. The iterative virtuous cycle can further comprise pre-operative, intra-operative, and post-operative techniques or processes. For example, the iterative virtuous cycle can comprise imaging analysis, case simulation, implant production, case support, data collection, machine learning, and/or predictive modeling. One or more techniques or processes of the iterative virtuous cycle can be repeated.