JP2017516066A - 二次性副甲状腺機能亢進症のリスク因子を決定するためのシステムおよび方法 - Google Patents

二次性副甲状腺機能亢進症のリスク因子を決定するためのシステムおよび方法 Download PDF

Info

Publication number
JP2017516066A
JP2017516066A JP2016549735A JP2016549735A JP2017516066A JP 2017516066 A JP2017516066 A JP 2017516066A JP 2016549735 A JP2016549735 A JP 2016549735A JP 2016549735 A JP2016549735 A JP 2016549735A JP 2017516066 A JP2017516066 A JP 2017516066A
Authority
JP
Japan
Prior art keywords
shpt
patient
risk factor
risk
computer system
Prior art date
Legal status (The legal status 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 status listed.)
Withdrawn
Application number
JP2016549735A
Other languages
English (en)
Japanese (ja)
Other versions
JP2017516066A5 (enExample
Inventor
アルギュロポウロス，クリストス
クセノス，コンスタンティノス
Original Assignee
アッヴィ・インコーポレイテッド
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
Application filed by アッヴィ・インコーポレイテッド filed Critical アッヴィ・インコーポレイテッド
Publication of JP2017516066A publication Critical patent/JP2017516066A/ja
Publication of JP2017516066A5 publication Critical patent/JP2017516066A5/ja
Withdrawn legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/74—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving hormones or other non-cytokine intercellular protein regulatory factors such as growth factors, including receptors to hormones and growth factors
    • G01N33/78—Thyroid gland hormones, e.g. T3, T4, TBH, TBG or their receptors
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/04—Endocrine or metabolic disorders
    • G01N2800/046—Thyroid disorders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/50—Determining the risk of developing a disease
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Pathology (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Immunology (AREA)
  • General Health & Medical Sciences (AREA)
  • Hematology (AREA)
  • Endocrinology (AREA)
  • Urology & Nephrology (AREA)
  • Chemical & Material Sciences (AREA)
  • Biotechnology (AREA)
  • Food Science & Technology (AREA)
  • Primary Health Care (AREA)
  • Epidemiology (AREA)
  • Microbiology (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Cell Biology (AREA)
  • Medicinal Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Physics & Mathematics (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Medical Treatment And Welfare Office Work (AREA)
JP2016549735A 2014-02-04 2015-02-03 二次性副甲状腺機能亢進症のリスク因子を決定するためのシステムおよび方法 Withdrawn JP2017516066A (ja)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US201461935593P 2014-02-04 2014-02-04
US61/935,593 2014-02-04
US14/612,109 2015-02-02
US14/612,109 US20150220698A1 (en) 2014-02-04 2015-02-02 Systems and methods for determining secondary hyperparathyroidism risk factors
PCT/US2015/014188 WO2015119915A1 (en) 2014-02-04 2015-02-03 Systems and methods for determining secondary hyperparathyroidism risk factors

Publications (2)

Publication Number Publication Date
JP2017516066A true JP2017516066A (ja) 2017-06-15
JP2017516066A5 JP2017516066A5 (enExample) 2018-03-01

Family

ID=53755064

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2016549735A Withdrawn JP2017516066A (ja) 2014-02-04 2015-02-03 二次性副甲状腺機能亢進症のリスク因子を決定するためのシステムおよび方法

Country Status (5)

Country Link
US (1) US20150220698A1 (enExample)
EP (1) EP3102952A1 (enExample)
JP (1) JP2017516066A (enExample)
HK (1) HK1231557A1 (enExample)
WO (1) WO2015119915A1 (enExample)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021192163A (ja) * 2020-06-05 2021-12-16 株式会社コスミックコーポレーション 生体情報評価システム及び生体情報評価プログラム
JP2024527790A (ja) * 2021-07-29 2024-07-26 サイロスコープ インコーポレイテッド 被験者の甲状腺機能異常症を予測するための方法及びシステム

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10796802B1 (en) * 2015-05-01 2020-10-06 Cerner Innovations, Inc. Computer decision support for determining surgery candidacy in stage four chronic kidney disease
US10600067B2 (en) * 2016-06-16 2020-03-24 Accenture Global Solutions Limited Demographic based adjustment of data processing decision results
WO2019032746A1 (en) * 2017-08-08 2019-02-14 Fresenius Medical Care Holdings, Inc. SYSTEMS AND METHODS FOR TREATING AND ESTIMATING THE PROGRESSION OF CHRONIC RENAL DISEASE
US11238989B2 (en) * 2017-11-08 2022-02-01 International Business Machines Corporation Personalized risk prediction based on intrinsic and extrinsic factors
CN115334977B (zh) * 2020-03-27 2025-11-28 泰尔茂株式会社 生物体功能推定装置及生物体功能推定方法

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021192163A (ja) * 2020-06-05 2021-12-16 株式会社コスミックコーポレーション 生体情報評価システム及び生体情報評価プログラム
JP2024527790A (ja) * 2021-07-29 2024-07-26 サイロスコープ インコーポレイテッド 被験者の甲状腺機能異常症を予測するための方法及びシステム
JP7556660B2 (ja) 2021-07-29 2024-09-26 サイロスコープ インコーポレイテッド 被験者の甲状腺機能異常症を予測するための方法及びシステム

Also Published As

Publication number Publication date
HK1231557A1 (zh) 2017-12-22
US20150220698A1 (en) 2015-08-06
WO2015119915A1 (en) 2015-08-13
EP3102952A1 (en) 2016-12-14

Similar Documents

Publication Publication Date Title
JP2017516066A (ja) 二次性副甲状腺機能亢進症のリスク因子を決定するためのシステムおよび方法
US11664126B2 (en) Clinical predictor based on multiple machine learning models
Maziarz et al. On longitudinal prediction with time-to-event outcome: comparison of modeling options
JP5681712B2 (ja) 臨床診断プロセスのシグマを求めるためのコンピュータで実施される方法およびシステム
US11404166B2 (en) Systems and methods for mining of medical data
US20250273333A1 (en) Methods and Apparatus for Diagnosis of Progressive Kidney Function Decline Using a Machine Learning Model
KR20110003352A (ko) 임상 결과를 평가하기 위한 방법 및 시스템
Kadatz et al. Predicting progression in CKD: perspectives and precautions
Hayes et al. Illness severity scores in veterinary medicine: what can we learn?
CN116313106A (zh) 肝硬化患者门静脉血栓预测模型及网络计算器的构建方法
KR20200135444A (ko) 만성 신장 질환의 위험에 대해 피험자를 스크리닝하기 위한 방법들 및 컴퓨터-구현 방법
Zheng et al. Adopting nested case–control quota sampling designs for the evaluation of risk markers
US20250182902A1 (en) Systems and methods for predicting outcomes for a lung undergoing an ex vivo lung perfusion
Azizmalayeri et al. Enhancing quality of care assessments: Managing atypical patients in ICU benchmarking in The Netherlands
US10971267B2 (en) Systems and methods for aggregation of automatically generated laboratory test results
US20250391573A1 (en) Generating a composite result using inflammation data
Bahrampour et al. Long-Term Survival of Patient with End-Stage Renal Disease Using Bayesian Mixture Cure Rate Frailty Models
Rajendran et al. Predictive accuracy of velocity time integral in predicting in-hospital outcomes in patients with intermediate-risk pulmonary embolism: a systematic review and meta-analysis
Kinikar et al. Converging Diagnostic Paths: A Unified Approach to Acid-Base Imbalances in COPD Patients
EP4677626A1 (en) Methods and systems for medical condition risk prediction and prediction triggering
Pretz et al. Longitudinal Assessment of Circulating Tumor DNA: A Proposed Statistical Framework
Bakker Developing cost-effective analytics for healthcare
Machiraju et al. Statistical approaches in ambispective cohort studies: Challenges and methodological insights
Ahmed Survival analysis for cardiothoracic surgeons: part 6-interpreting time-to-event data
CN118824450A (zh) 适用于多源医疗系统采集的规则模型生成方法、系统、设备、介质及程序产品

Legal Events

Date Code Title Description
A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20180117

A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20180117

A761 Written withdrawal of application

Free format text: JAPANESE INTERMEDIATE CODE: A761

Effective date: 20180815