Post-Selection Confidence Bounds for Prediction Performance

In machine learning, the selection of a promising model from a potentially large number of competing models and the assessment of its generalization performance are critical tasks that need careful consideration. Typically, model selection and evaluation are strictly separated endeavors, splitting the sample at hand into a training, validation, and evaluation set, and only compute a single confidence interval for the prediction performance of the final selected model. We however propose an algorithm how to compute valid lower confidence bounds for multiple models that have been selected based on their prediction performances in the evaluation set by interpreting the selection problem as a simultaneous inference problem. We use bootstrap tilting and a maxT-type multiplicity correction. The approach is universally applicable for any combination of prediction models, any model selection strategy, and any prediction performance measure that accepts weights. We conducted various simulation experiments which show that our proposed approach yields lower confidence bounds that are at least comparably good as bounds from standard approaches, and that reliably reach the nominal coverage probability. In addition, especially when sample size is small, our proposed approach yields better performing prediction models than the default selection of only one model for evaluation does.Comment: Changed title, changed layout of figures, added a number to equation 4, added more info to figure captions, added keyword

Cost-Effectiveness of MR-Mammography in Breast Cancer Screening of Women With Extremely Dense Breasts After Two Rounds of Screening

Objectives: To evaluate the cost-effectiveness of MR-mammography (MRM) vs. x-ray based mammography (XM) in two-yearly screening women of intermediate risk for breast cancer in the light of recent literature. Methods: Decision analysis and Markov modelling were used to compare cumulative costs (in US-$) and outcomes (in QALYs) of MRM vs. XM over the model runtime of 20 years. The perspective of the U.S. healthcare system was selected. Incremental cost-effectiveness ratios (ICER) were calculated and related to a willingness to pay-threshold of$ 100,000 per QALY in order to evaluate the cost-effectiveness. Deterministic and probabilistic sensitivity analyses were conducted to test the impact of variations of the input parameters. In particular, variations of the rate of false positive findings beyond the first screening round and their impact on cost-effectiveness were assessed. Results: Breast cancer screening with MRM resulted in increased costs and superior effectiveness. Cumulative average costs of $6,081 per woman and cumulative effects of 15.12 QALYs were determined for MRM, whereas screening with XM resulted in costs of$ 5,810 and 15.10 QALYs, resulting in an ICER of $13,493 per QALY gained. When the specificity of MRM in the second and subsequent screening rounds was varied from 92$ 38,849 to $ 5,062 per QALY. Conclusions: Based on most recent data on the diagnostic performance beyond the first screening round, MRM may remain the economically preferable alternative in screening women of intermediate risk for breast cancer due to their dense breast tissue

Mass tagging:Verification and calibration of particle identification by high-resolution mass measurements

The access to exotic nuclei at radioactive ion beam facilities is crucial for the state of the art research across several fields of physics such as in nuclear structure, the understanding of fundamental interactions and nuclear astrophysics. The particle identification is of high importance, besides the challenging production of these rare and short-lived nuclei. At in-flight facilities, the particle identification is based on measuring the time-of-flight, energy-deposition and magnetic rigidity. These quantities are calibrated to convert them into A/Q and Z of the ions. To ensure a correct calibration, the unambiguous identification, also called tagging, of one species is necessary. Here, we present a novel tagging method by high-resolution mass measurements using an MR-TOF-MS after thermalization of the ions in a cryogenic stopping cell. The method was successfully established and tested at the fragment separator FRS at GSI with the FRS Ion Catcher in experiments using different FRS operation modes.</p

Studying Gamow-Teller transitions and the assignment of isomeric and ground states at N=50

Direct mass measurements of neutron-deficient nuclides around the N = 50 shell closure below 100Sn were performed at the FRS Ion Catcher (FRS-IC) at GSI, Germany. The nuclei were produced by projectile fragmentation of 124Xe, separated in the fragment separator FRS and delivered to the FRS-IC. The masses of 14 ground states and two isomers were measured with relative mass uncertainties down to 1 x 10-7 using the multiple-reflection time-of-flight mass spectrometer of the FRS-IC, including the first direct mass measurements of 98Cd , 97Rh. A new QEC = 5437 +/- 67 keV was obtained for 98Cd, resulting in a summed Gamow-Teller (GT) strength for the five observed transitions (0+ --> 1+) as B(GT) = 2.94+0.32 -0.28. Investigation of this result in state-of-the-art shell model approaches accounting for the first time experimentally observed spectrum of GT transitions points to a perfect agreement for N = 50 isotones. The excitation energy of the long-lived isomeric state in 94Rh was determined for the first time to be 293 +/- 21 keV. This, together with the shell model calculations, allows the level ordering in 94Rh to be understood.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/). Funded by SCOAP3.Peer reviewe