Uncertainty evaluation associated with versatile automated gauging influenced by process variations through design of experiments approach

Recent advances in versatile automated gauging have enabled accurate geometric tolerance assessment on the shop floor. This paper is concerned with the uncertainty evaluation associated with comparative coordinate measurement using the design of experiments (DOE) approach. It employs the Renishaw Equator which is a software-driven comparative gauge based on the traditional comparison of production parts to a reference master part. The fixturing requirement of each production part to the master part is approximately ±1 mm for a comparison process with an uncertainty of ±2 μm. Therefore, a number of experimental designs are applied with the main focus on the influence of part misalignment from rotation between master and measure coordinate frames on the comparator measurement uncertainty. Other factors considered include measurement mode mainly in scanning and touch-trigger probing (TTP) and alignment procedure used to establish the coordinate reference frame (CRF) with respect to the number of contact points used for each geometric feature measured. The measurement uncertainty analysis of the comparator technique used by the Equator gauge commences with a simple measurement task using a gauge block to evaluate the three-dimensional (3D) uncertainty of length comparative coordinate measurement influenced by an offset by tilt in one direction (two-dimensional angular misalignment). Then, a specific manufactured measurement object is employed so that the comparator measurement uncertainty can be assessed for numerous measurement tasks within a satisfactory range of the working volume of the versatile gauge. Furthermore, in the second case study, different types of part misalignment including both 2D and 3D angular misalignments are applied. The time required for managing the re-mastering process is also examined. A task specific uncertainty evaluation is completed using DOE. Also, investigating the effects of process variations that might be experienced by such a device in workshop environments. It is shown that the comparator measurement uncertainties obtained by all the experiments agree with system features under specified conditions. It is also demonstrated that when the specified conditions are exceeded, the comparator measurement uncertainty is associated with the measurement task, the measurement strategy used, the feature size, and the magnitude and direction of offset angles in relation to the reference axes of the machine. In particular, departures from the specified part fixturing requirement of Equator have a more significant effect on the uncertainty of length measurement in comparator mode and a less significant effect on the diameter measurement uncertainty for the specific Equator and test conditions

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

CT coronary angiography in patients with suspected angina due to coronary heart disease (SCOT-HEART): an open-label,parallel-group, multicentre trial

Background The benefi t of CT coronary angiography (CTCA) in patients presenting with stable chest pain has not been systematically studied. We aimed to assess the eff ect of CTCA on the diagnosis, management, and outcome of patients referred to the cardiology clinic with suspected angina due to coronary heart disease. Methods In this prospective open-label, parallel-group, multicentre trial, we recruited patients aged 18–75 years referred for the assessment of suspected angina due to coronary heart disease from 12 cardiology chest pain clinics across Scotland. We randomly assigned (1:1) participants to standard care plus CTCA or standard care alone. Randomisation was done with a web-based service to ensure allocation concealment. The primary endpoint was certainty of the diagnosis of angina secondary to coronary heart disease at 6 weeks. All analyses were intention to treat, and patients were analysed in the group they were allocated to, irrespective of compliance with scanning. This study is registered with ClinicalTrials.gov, number NCT01149590. Findings Between Nov 18, 2010, and Sept 24, 2014, we randomly assigned 4146 (42%) of 9849 patients who had been referred for assessment of suspected angina due to coronary heart disease. 47% of participants had a baseline clinic diagnosis of coronary heart disease and 36% had angina due to coronary heart disease. At 6 weeks, CTCA reclassifi ed the diagnosis of coronary heart disease in 558 (27%) patients and the diagnosis of angina due to coronary heart disease in 481 (23%) patients (standard care 22 [1%] and 23 [1%]; p<0·0001). Although both the certainty (relative risk [RR] 2·56, 95% CI 2·33–2·79; p<0·0001) and frequency of coronary heart disease increased (1·09, 1·02–1·17; p=0·0172), the certainty increased (1·79, 1·62–1·96; p<0·0001) and frequency seemed to decrease (0·93, 0·85–1·02; p=0·1289) for the diagnosis of angina due to coronary heart disease. This changed planned investigations (15% vs 1%; p<0·0001) and treatments (23% vs 5%; p<0·0001) but did not aff ect 6-week symptom severity or subsequent admittances to hospital for chest pain. After 1·7 years, CTCA was associated with a 38% reduction in fatal and nonfatal myocardial infarction (26 vs 42, HR 0·62, 95% CI 0·38–1·01; p=0·0527), but this was not signifi cant. Interpretation In patients with suspected angina due to coronary heart disease, CTCA clarifi es the diagnosis, enables targeting of interventions, and might reduce the future risk of myocardial infarction. Funding The Chief Scientist Offi ce of the Scottish Government Health and Social Care Directorates funded the trial with supplementary awards from Edinburgh and Lothian’s Health Foundation Trust and the Heart Diseases Research Fund

Role of multidetector computed tomography in the diagnosis and management of patients attending the rapid access chest pain clinic, The Scottish computed tomography of the heart (SCOT-HEART) trial:study protocol for randomized controlled trial

&lt;p&gt;Background: Rapid access chest pain clinics have facilitated the early diagnosis and treatment of patients with coronary heart disease and angina. Despite this important service provision, coronary heart disease continues to be under-diagnosed and many patients are left untreated and at risk. Recent advances in imaging technology have now led to the widespread use of noninvasive computed tomography, which can be used to measure coronary artery calcium scores and perform coronary angiography in one examination. However, this technology has not been robustly evaluated in its application to the clinic.&lt;/p&gt; &lt;p&gt;Methods/design: The SCOT-HEART study is an open parallel group prospective multicentre randomized controlled trial of 4,138 patients attending the rapid access chest pain clinic for evaluation of suspected cardiac chest pain. Following clinical consultation, participants will be approached and randomized 1:1 to receive standard care or standard care plus ≥64-multidetector computed tomography coronary angiography and coronary calcium score. Randomization will be conducted using a web-based system to ensure allocation concealment and will incorporate minimization. The primary endpoint of the study will be the proportion of patients diagnosed with angina pectoris secondary to coronary heart disease at 6 weeks. Secondary endpoints will include the assessment of subsequent symptoms, diagnosis, investigation and treatment. In addition, long-term health outcomes, safety endpoints, such as radiation dose, and health economic endpoints will be assessed. Assuming a clinic rate of 27.0% for the diagnosis of angina pectoris due to coronary heart disease, we will need to recruit 2,069 patients per group to detect an absolute increase of 4.0% in the rate of diagnosis at 80% power and a two-sided P value of 0.05. The SCOT-HEART study is currently recruiting participants and expects to report in 2014.&lt;/p&gt; &lt;p&gt;Discussion: This is the first study to look at the implementation of computed tomography in the patient care pathway that is outcome focused. This study will have major implications for the management of patients with cardiovascular disease.&lt;/p&gt