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Rainbow Schlieren Deflectometry for spherical fields: A new algorithm and numerical validation approach

NUMERICAL HEAT TRANSFER PART B-FUNDAMENTALS 2024年第9期85卷 1178-1201页

作者： Junne, Henning Jurtz, Nico Schulz, Joschka M. Kraume, Matthias Boehm, Lutz Tech Univ Berlin Chair Chem & Proc Engn D-10587 Berlin Germany

The authors present a new algorithm for analyzing ray deflection within spherical refractive index fields. The algorithm emanates from the well-known deconvolution algorithm for axisymmetric refractive index fields using the inverse Abel transformation and can be used for experimental Rainbow Schlieren Deflectometry (RSD) data. It was numerically validated by Computational Fluid Dynamics (CFD) calculations of free convection around an isothermal sphere and successive ray tracing through the determined temperature field. The algorithm determined radial temperature profiles and local Nusselt numbers from resulting deflection angles of the ray tracing simulations. An excellent agreement between original and reconstructed temperature field within the limits of assumptions was reached. This proves the usability of the algorithm for the experimental determination of spherical refractive index fields from future heat or mass transfer experiments.

关键词： algorithm validation free convection rainbow Schlieren deflectometry ray tracing spherical refractive index fields

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A Data-Driven algorithm to Recommend Initial Clinical Workup for Outpatient Specialty Referral: algorithm Development and validation Using Electronic Health Record Data and Expert Surveys

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JMIR MEDICAL INFORMATICS 2022年第3期10卷 e30104页

作者： Ip, Wui Prahalad, Priya Palma, Jonathan Chen, Jonathan H. Stanford Univ Dept Pediat Sch Med 453 Quarry RdMC 5660 Palo Alto CA 94304 USA Orlando Hlth Winnie Palmer Hosp Women & Babies Neonatol & Perinatal Med Orlando FL USA Stanford Univ Dept Med Sch Med Palo Alto CA 94304 USA Stanford Ctr Biomed Informat Res Stanford CA USA

Background: Millions of people have limited access to specialty care. The problem is exacerbated by ineffective specialty visits due to incomplete prereferral workup, leading to delays in diagnosis and treatment. Existing processes to guide prereferral diagnostic workup are labor-intensive (ie, building a consensus guideline between primary care doctors and specialists) and require the availability of the specialists (ie, electronic consultation). Objective: Using pediatric endocrinology as an example, we develop a recommender algorithm to anticipate patients' initial workup needs at the time of specialty referral and compare it to a reference benchmark using the most common workup orders. We also evaluate the clinical appropriateness of the algorithm recommendations. Methods: Electronic health record data were extracted from 3424 pediatric patients with new outpatient endocrinology referrals at an academic institution from 2015 to 2020. Using item co-occurrence statistics, we predicted the initial workup orders that would be entered by specialists and assessed the recommender's performance in a holdout data set based on what the specialists actually ordered. We surveyed endocrinologists to assess the clinical appropriateness of the predicted orders and to understand the initial workup process. Results: Specialists (n=12) indicated that <50% of new patient referrals arrive with complete initial workup for common referral reasons. The algorithm achieved an area under the receiver operating characteristic curve of 0.95 (95% CI 0.95-0.96). Compared to a reference benchmark using the most common orders, precision and recall improved from 37% to 48% (P<.001) and from 27% to 39% (P<.001) for the top 4 recommendations, respectively. The top 4 recommendations generated for common referral conditions (abnormal thyroid studies, obesity, amenorrhea) were considered clinically appropriate the majority of the time by specialists surveyed and practice guidelines reviewed. Conclus

关键词： recommender system electronic health records clinical decision support specialty consultation machine learning EHR algorithm algorithm development algorithm validation automation prediction patient needs

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Synthetic sequences and ground-truth flow field generation for algorithm validation

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MULTIMEDIA TOOLS AND APPLICATIONS 2015年第9期74卷 3121-3135页

作者： Onkarappa, Naveen Sappa, Angel D. Autonomous Univ Barcelona Comp Vis Ctr E-08193 Barcelona Spain Comp Vis Ctr Barcelona 08193 Spain

Research in computer vision is advancing by the availability of good datasets that help to improve algorithms, validate results and obtain comparative analysis. The datasets can be real or synthetic. For some of the computer vision problems such as optical flow it is not possible to obtain ground-truth optical flow with high accuracy in natural outdoor real scenarios directly by any sensor, although it is possible to obtain ground-truth data of real scenarios in a laboratory setup with limited motion. In this difficult situation computer graphics offers a viable option for creating realistic virtual scenarios. In the current work we present a framework to design virtual scenes and generate sequences as well as ground-truth flow fields. Particularly, we generate a dataset containing sequences of driving scenarios. The sequences in the dataset vary in different speeds of the on-board vision system, different road textures, complex motion of vehicle and independent moving vehicles in the scene. This dataset enables analyzing and adaptation of existing optical flow methods, and leads to invention of new approaches particularly for driver assistance systems.

关键词： Ground-truth optical flow Synthetic sequence algorithm validation

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validation of an algorithm to Identify Venous Thromboembolism in Health Insurance Claims Data Among Patients with Rheumatoid Arthritis

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CLINICAL EPIDEMIOLOGY 2023年 15卷 671-682页

作者： Kim, Sangmi Martin, Carolyn White, John Carlyle, Maureen Bui, Bonnie Gao, Shiyao Salinas, Claudia A. Eli Lilly & Co Global Patient Safety Pharmacoepidemiol Indianapolis IN USA Optum Life Sci Hlth Econ & Outcomes Res Eden Prairie MN USA Eli Lilly & Co Lilly Corp Ctr Global Patient Safety Pharmacoepidemiol 893 Delaware St Indianapolis IN 46285 USA

Purpose: Health insurance claims databases provide an opportunity to study uncommon events, such as venous thromboembolism (VTE), in large patient populations. This study evaluated case definitions for identifying VTE among patients treated for rheumatoid arthritis (RA) using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes in claims data. Patients and Methods: Study participants were insured adults who received treatment for and had a diagnosis of RA between 2016 and 2020. After a 6-month covariate assessment window, patients were observed for >= 1 month until health plan disenrollment, occurrence of a presumptive VTE, or end of the study (12/31/2020). Presumptive VTEs were identified using predefined algorithms based on ICD-10-CM diagnosis codes, anticoagulant use, and care setting. Medical charts were abstracted to confirm the VTE diagnosis. Performance of primary and secondary (less stringent) algorithms was assessed by calculating the positive predictive value (PPV;primary and secondary objectives). Additionally, a linked electronic health record (EHR) claims database and abstracted provider notes were used as a novel alternative source to validate claims-based outcome definitions (exploratory objective). Results: A total of 155 charts identified with the primary VTE algorithm were abstracted. The majority of patients were female (73.5%), with mean (standard deviation) age 66.4 (10.7) years and Medicare insurance (80.6%). Obesity (46.8%), ever smoking (55.8%), and prior evidence of VTE (28.4%) were commonly reported in medical charts. The PPV for the primary VTE algorithm was 75.5% (117/155;95% confidence interval [CI], 68.7%, 82.3%). A less stringent secondary algorithm had a PPV of 52.6% (40/76;95% CI, 41.4%, 63.9%). Using an alternative EHR-linked claims database, the primary VTE algorithm PPV was lower, potentially due to the unavailability of relevant records for validation. Conclusion: Administrative claims

关键词： algorithm validation rheumatoid arthritis venous thromboembolism positive predictive value administrative claims data ICD-10-CM

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Initial independent validation of a genomic heart failure survival prediction algorithm

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EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2021年第2期6卷 139-145页

作者： Bondar, Galyna Silacheva, Irina Bao, Tra-Mi Deshmukh, Sumeet Kulkarni, Neha S. Nakade, Taisuke Grogan, Tristan Elashoff, David Deng, Mario C. Univ Calif Los Angeles David Geffen Sch Med Med Ctr Dept MedDiv Cardiol Los Angeles CA 90095 USA LeukoLifeDx Inc Rumson NJ USA Univ Sheffield Dept Mol Biol & Biotechnol Sheffield S Yorkshire England Univ Sheffield Acad Unit Reprod & Dev Med Sheffield S Yorkshire England

Background: Biological determinants of survival in advanced heart failure (AdHF) are linked to systems biological properties of disease severity including age, comorbidities, and frailty. We hypothesize that an algorithm trained to predict the survival in severely ill mechanical circulatory support (MCS) AdHF patients can be independently validated in AdHF-cohorts of varying severity undergoing etiology-specific interventions including heart transplantation (HTx), transcatheter aortic valve replacement (TAVR), and continued guidelines directed medical therapy (GDMT). Research Design & Methods: We independently validated our previously published multi-dimensional algorithm, based on 4 clinical parameters and 12 transcriptomic biomarkers, and trained in AdHF patients undergoing MCS-surgery (n = 29), in AdHF patients undergoing TAVR, HTx, MCS, and GDMT-interventions (n = 48). Results: In the independent validation cohort, our algorithm demonstrated 71% sensitivity, 90% specificity, 56% positive predictive value, and 95% negative predictive value, allowing for construction of a prototype survival prediction score. While prediction of 1-year survival using clinical parameters alone achieved an AUC = 0.69, addition of 12 differentially expressed genes to the clinical model improved the AUC = 0.90. Conclusions: Our initial validation data suggests that the proposed multi-dimensional algorithm is applicable across various AdHF-risk groups and Surgical-Interventional Therapies (S/IT), increasing survival prediction accuracy compared to clinical data alone and warranting further study in larger cohorts.

关键词： Advanced heart failure algorithm validation heart failure interventional therapies mechanical circulatory support survival prediction transcriptomic biomarker

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validation of case definition algorithms for the ascertainment of congenital anomalies

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BIRTH DEFECTS RESEARCH 2023年第3期115卷 302-317页

作者： de Escalante, Yonabeth Nava Abayomi, Aanu Langlois, Sylvie Ye, Xibiao Erickson, Anders Ngo, Henry Armour, Rosemary Okamoto, Reiko Arbour, Laura Bedard, Tanya Der, Kenny Van Allen, Margot Skarsgard, Erik Lavoie, Martin Henry, Bonnie British Columbia Minist Hlth Victoria BC Canada Univ British Columbia Fac Med Dept Med Genet Vancouver BC Canada Univ Victoria Hlth Informat Sci Vancouver BC Canada Prov Hlth Serv Author Perinatal Serv British Columbia Vancouver BC Canada British Columbia Vital Stat Agcy Vancouver BC Canada Natl Res Council Canada Digital Technol Res Ctr Ottawa ON Canada Univ Victoria Community Genet Res Program Isl Med Program Victoria BC Canada Alberta Hlth Hlth Stand Qual & Performance Edmonton AB Canada Vancouver Isl Hlth Author Med Genet Vancouver BC Canada British Columbia Childrens Hosp Dept Surg Vancouver BC Canada Univ British Columbia Sch Populat & Publ Hlth Vancouver BC Canada

Background Congenital anomalies (CA) are one of the leading causes of infant mortality and long-term disability. Many jurisdictions rely on health administrative data to monitor these conditions. Case definition algorithms can be used to monitor CA;however, validation of these algorithms is needed to understand the strengths and limitations of the data. This study aimed to validate case definition algorithms used in a CA surveillance system in British Columbia (BC), Canada. Methods A cohort of births between March 2000 and April 2002 in BC was linked to the Health Status Registry (HSR) and the BC Congenital Anomalies Surveillance System (BCCASS) to identify cases and non-cases of specific anomalies within each surveillance system. Measures of algorithm performance were calculated for each CA using the HSR as the reference standard. Agreement between both databases was calculated using kappa coefficient. The modified Standards for Reporting Diagnostic Accuracy guidelines were used to enhance the quality of the study. Results Measures of algorithm performance varied by condition. Positive predictive value (PPV) ranged between approximately 73%-100%. Sensitivity was lower than PPV for most conditions. Internal congenital anomalies or conditions not easily identifiable at birth had the lowest sensitivity. Specificity and negative predictive value exceeded 99% for all algorithms. Conclusion Case definition algorithms may be used to monitor CA at the population level. Accuracy of algorithms is higher for conditions that are easily identified at birth. Jurisdictions with similar administrative data may benefit from using validated case definitions for CA surveillance as this facilitates cross-jurisdictional comparison.

关键词： algorithm validation congenital anomalies health administrative data surveillance validation study

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Application analysis of a new pre-localization series algorithm for differentiating wide QRS complex tachycardia

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JOURNAL OF ELECTROCARDIOLOGY 2025年 91卷 153937-153937页

作者： Ni, Honglin Huang, Yue Pan, Xiaowei Zhang, Xiaoli Xu, Lifang Wang, Zhiyong Zhai, Changlin Pan, Haihua Jiaxing Univ Hosp 1 Jiaxing Affiliated Hosp Dept Electrocardiol Jiaxing 314001 Peoples R China Jiaxing Univ Hosp 1 Jiaxing Affiliated Hosp Dept Cardiol 1882 Zhonghuan South Rd Jiaxing 314001 Zhejiang Peoples R China

Background: Accurate diagnosis of wide QRS complex tachycardia (WCT) holds significant clinical value for further diagnosis and treatment. Objective: To evaluate a new WCT differentiation algorithm, defined as the pre-localization series algorithm, which includes the series process for differentiating ventricular tachycardia (VT) from supraventricular tachycardia (SVT) and differentiating VT from preexcited tachycardia (PXT). Methods: A retrospective analysis of electrocardiograms (ECGs) from 185 patients with WCT was conducted using the pre-localization single-process algorithm (differentiating VT from SVT without differentiating VT from PXT), the pre-localization series algorithm, the limb lead algorithm, and the Basel algorithm. The ECGs were differentiated into VT or SVT. The pre-localization series algorithm further differentiated the initially diagnosed VT into VT or PXT, and the results were compared with the confirmed diagnoses to assess the diagnostic value of the four algorithms. Results: The pre-localization single-process algorithm had higher AUC values (0.777 vs. 0.711 vs. 0.646), sensitivity (0.955 vs. 0.809 vs. 0.745), and accuracy (0.811 vs. 0.730 vs. 0.665) compared with the limb lead algorithm and the Basel algorithm. The pre-localization series algorithm had higher AUC values (0.901 vs. 0.711 vs. 0.646), sensitivity (0.909 vs. 0.809 vs. 0.745), specificity (0.893 vs. 0.613 vs. 0.547), and accuracy (0.903 vs. 0.730 vs. 0.665) compared with the limb lead algorithm and the Basel algorithm, the pre-localization series algorithm also had higher specificity (0.893 vs. 0.600) and accuracy (0.903 vs. 0.811) than the pre-localization single-process algorithm, but sensitivity(0.909 vs. 0.955) was slightly lower, with statistically significant differences (all P < 0.05). Conclusion: The pre-localization single-process algorithm had higher sensitivity and accuracy compared with the limb lead algorithm and the Basel algorithm. The series algorithm, due to its

关键词： Wide QRS complex tachycardia Pre-localization series algorithm Limb lead algorithm Basel algorithm algorithm validation

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Combined digital media technology and advanced computing science in folk art design application

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SYSTEMS AND SOFT COMPUTING 2025年 7卷

作者： Fu, Xingxing Hebi Automot Engn Profess Coll Dept Econ & Management Hebi 458030 Peoples R China

With the continuous development of intelligent computer technology, its application in the field of art and design is becoming increasingly widespread. However, the current application of artificial intelligence technology in folk art design is relatively simple and lacks systematic analysis methods. Therefore, this study aims to construct an optimization model through the use of advanced computational science methods and digital media technology to achieve a comprehensive analysis of various indicators of folk art design. This study uses watermark verification theory and digital models to analyze folk art design, and constructs corresponding optimization models through parameter encoded verification curves and calculations of different indicators. This model can conduct targeted analysis for different indicators to obtain corresponding calculation results. The experimental results show that the model calculation results exhibit relatively significant fluctuations in design concepts and public aesthetics, indicating that these two factors have a significant impact on the model. The design strategy presents a linear variation, with a relatively small range of changes in overall aesthetics and color elements, and a relatively small impact on the calculation results. In addition, the validation coefficient has an effect when the independent variable is small, while larger independent variables have an inhibitory effect on the validation coefficient. This study achieved a comprehensive analysis of various indicators of folk art design by constructing an optimization model. The effectiveness and accuracy of the model have been verified through comparison with experimental data.

关键词： Digital media technology Advanced computing science Watermark image Mathematical model algorithm validation

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Development of electronic health record based algorithms to identify individuals with diabetic retinopathy

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2024年第11期31卷 2560-2570页

作者： Breeyear, Joseph H. Mitchell, Sabrina L. Nealon, Cari L. Hellwege, Jacklyn N. Charest, Brian Khakharia, Anjali Halladay, Christopher W. Yang, Janine Garriga, Gustavo A. Wilson, Otis D. Basnet, Til B. Hung, Adriana M. Reaven, Peter D. Meigs, James B. Rhee, Mary K. Sun, Yang Lynch, Mary G. Sobrin, Lucia Brantley Jr, Milam A. Sun, Yan, V Wilson, Peter W. Iyengar, Sudha K. Peachey, Neal S. Phillips, Lawrence S. Edwards, Todd L. Giri, Ayush Vanderbilt Univ Dept Med Div Epidemiol Med Ctr Nashville TN 37232 USA VA Tennessee Valley Healthcare Syst 626 Nashville TN 37212 USA Vanderbilt Univ Dept Ophthalmol & Visual Sci Med Ctr Nashville TN 37232 USA VA Northeast Ohio Healthcare Syst Eye Clin Cleveland OH 44106 USA Vanderbilt Univ Vanderbilt Genet Inst Nashville TN 37232 USA Vanderbilt Univ Dept Med Div Genet Med Med Ctr Nashville TN 37232 USA VA Boston Healthcare Syst Massachusetts Vet Epidemiol Res & Informat Ctr MAV Boston MA 02111 USA VA Atlanta Healthcare Syst Decatur GA 30033 USA Emory Univ Dept Med & Geriatr Sch Med Atlanta GA 30307 USA Providence VA Med Ctr Providence RI 02908 USA Harvard Med Sch Mass Eye & Ear Infirm Dept Ophthalmol Boston MA 02114 USA Vanderbilt Univ Med Ctr Dept Obstet & Gynecol Div Quantitat & Clin Sci Nashville TN 37232 USA Vanderbilt Univ Med Ctr Dept Med Div Nephrol & Hypertens Nashville TN 37232 USA Phoenix VA Hlth Care Syst Phoenix AZ 85012 USA Univ Arizona Coll Med Phoenix AZ 85721 USA Broad Inst Program Med & Populat Genet Cambridge MA 02142 USA Harvard Med Sch Dept Med Boston MA 02115 USA Massachusetts Gen Hosp Div Gen Internal Med Boston MA 02114 USA Emory Univ Sch Med Dept Med Div Endocrinol Metab & Lipids Atlanta GA 30307 USA Stanford Univ Dept Ophthalmol Sch Med Palo Alto CA 94305 USA Emory Univ Rollins Sch Publ Hlth Dept Epidemiol Atlanta GA 30307 USA Emory Univ Dept Biomed Informat Sch Med Atlanta GA 30307 USA Emory Univ Sch Med Dept Med Div Cardiol Atlanta GA 30307 USA VA Northeast Ohio Healthcare Syst Res Serv Cleveland OH 44106 USA Case Western Reserve Univ Dept Populat & Quantitat Hlth Sci Sch Med Cleveland OH 44106 USA Cleveland Clin Cole Eye Inst Cleveland OH 44106 USA Case Western Reserve Univ Lerner Coll Med Dept Ophthalmol Cleveland Clin Cleveland OH 44195 USA

Objectives To develop, validate, and implement algorithms to identify diabetic retinopathy (DR) cases and controls from electronic health care records (EHRs).Materials and Methods We developed and validated electronic health record (EHR)-based algorithms to identify DR cases and individuals with type I or II diabetes without DR (controls) in 3 independent EHR systems: Vanderbilt University Medical Center Synthetic Derivative (VUMC), the VA Northeast Ohio Healthcare System (VANEOHS), and Massachusetts General Brigham (MGB). Cases were required to meet 1 of the following 3 criteria: (1) 2 or more dates with any DR ICD-9/10 code documented in the EHR, (2) at least one affirmative health-factor or EPIC code for DR along with an ICD9/10 code for DR on a different day, or (3) at least one ICD-9/10 code for any DR occurring within 24 hours of an ophthalmology examination. Criteria for controls included affirmative evidence for diabetes as well as an ophthalmology *** The algorithms, developed and evaluated in VUMC through manual chart review, resulted in a positive predictive value (PPV) of 0.93 for cases and negative predictive value (NPV) of 0.91 for controls. Implementation of algorithms yielded similar metrics in VANEOHS (PPV = 0.94;NPV = 0.86) and lower in MGB (PPV = 0.84;NPV = 0.76). In comparison, the algorithm for DR implemented in Phenome-wide association study (PheWAS) in VUMC yielded similar PPV (0.92) but substantially reduced NPV (0.48). Implementation of the algorithms to the Million Veteran Program identified over 62 000 DR cases with genetic data including 14 549 African Americans and 6209 Hispanics with ***/Discussion We demonstrate the robustness of the algorithms at 3 separate healthcare centers, with a minimum PPV of 0.84 and substantially improved NPV than existing automated methods. We strongly encourage independent validation and incorporation of features unique to each EHR to enhance algorithm performance for DR cases and

关键词： diabetes complications diabetic retinopathy algorithm development algorithm validation

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validation of algorithms to Identify Acute Myocardial Infarction, Stroke, and Cardiovascular Death in German Health Insurance Data

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CLINICAL EPIDEMIOLOGY 2022年 14卷 1351-1361页

作者： Platzbecker, Katharina Voss, Annemarie Reinold, Jonas Elbrecht, Anne Biewener, Wolfgang Prieto-Alhambra, Daniel Joedicke, Annika M. Schink, Tania Leibniz Inst Prevent Res & Epidemiol BIPS Dept Clin Epidemiol Bremen Germany Leibniz Inst Prevent Res & Epidemiol BIPS Dept Epidemiol Methods & Etiol Res Bremen Germany Univ Oxford Ctr Stat Med Nuffield Dept Orthopaed Pharmaco & Device Epidemiol Oxford England Erasmus MC Dept Med Informat Rotterdam Netherlands Leibniz Inst Prevent Res & Epidemiol BIPS Dept Clin Epidemiol Achterstr 30 D-28359 Bremen Germany

Purpose: validation of outcomes allows measurement of and correction for potential misclassification and targeted adjustment of algorithms for case definition. The purpose of our study was to validate algorithms for identifying cases of acute myocardial infarction (AMI), stroke, and cardiovascular (CV) death using patient profiles, ie, chronological tabular summaries of relevant available information on a patient, extracted from pseudonymized German claims *** and Methods: Based on the German Pharmacoepidemiological Research Database (GePaRD), 250 cases were randomly selected (50% males) for each outcome between 2016 and 2017 based on the inclusion criteria age >50 years and continuous insurance >1 year and applying the following algorithms: hospitalization with a main diagnosis of AMI (ICD-10-GM codes I21.-and I22.-) or stroke (I63, I61, I64) or death with a hospitalization in the 60 days before with a main diagnosis of CV disease. Patient profiles were built including (i) age and sex, (ii) hospitalizations incl. diagnoses, procedures, discharge reasons, (iii) outpatient diagnoses incl. diagnostic certainty, physician specialty, (iv) outpatient encounters, and (v) outpatient dispensings. Using adjudication criteria based on clinical guidelines and risk factors, two trained physicians independently classified cases as "certain", "probable", "unlikely" or "not assessable". Positive predictive values (PPVs) were calculated as percentage of confirmed cases among all assessable ***: For AMI, the overall PPV was 97.6% [95% confidence interval 94.8-99.1]. The PPV for any stroke was 94.8% [91.3-97.2] and higher for ischemic (98.3% [95.0-99.6]) than for hemorrhagic stroke (86.5% [76.5-93.3]). The PPV for CV death was 79.9% [74.4-84.4]. It increased to 91.7% [87.2-95.0] after excluding 32 cases with data insufficient for a ***: algorithms based on hospital diagnoses can identify AMI, stroke, and CV death from German claims data with high P

关键词： claims data algorithm validation patient profiles positive predictive value

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