Evaluating machine learning models in non-standard settings: An overview and new findings

Estimating the generalization error (GE) of machine learning models is fundamental, with resampling methods being the most common approach. However, in non-standard settings, particularly those where observations are not independently and identically distributed, resampling using simple random data divisions may lead to biased GE estimates. This paper strives to present well-grounded guidelines for GE estimation in various such non-standard settings: clustered data, spatial data, unequal sampling probabilities, concept drift, and hierarchically structured outcomes. Our overview combines well-established methodologies with other existing methods that, to our knowledge, have not been frequently considered in these particular settings. A unifying principle among these techniques is that the test data used in each iteration of the resampling procedure should reflect the new observations to which the model will be applied, while the training data should be representative of the entire data set used to obtain the final model. Beyond providing an overview, we address literature gaps by conducting simulation studies. These studies assess the necessity of using GE-estimation methods tailored to the respective setting. Our findings corroborate the concern that standard resampling methods often yield biased GE estimates in non-standard settings, underscoring the importance of tailored GE estimation

Reproducibility of 3-dimensional ultrasound readings of volume of carotid atherosclerotic plaque

<p>Abstract</p> <p>Background</p> <p>Non-invasive 3-dimensional (3D) ultrasound (US) has emerged as the predominant approach for evaluating the progression of carotid atherosclerosis and its response to treatment. The aim of this study was to investigate the quality of a central reading procedure concerning plaque volume (PV), measured by 3D US in a multinational US trial.</p> <p>Methods</p> <p>Two data sets of 45 and 60 3D US patient images of plaques (mean PV, 71.8 and 39.8 μl, respectively) were used. PV was assessed by means of manual planimetry. The intraclass correlation coefficient (ICC) was applied to determine reader variabilities. The repeatability coefficient (RC) and the coefficient of variation (CV) were used to investigate the effect of number of slices (S) in manual planimetry and plaque size on measurement variability.</p> <p>Results</p> <p>Intra-reader variability was small as reflected by ICCs of 0.985, 0.967 and 0.969 for 3 appointed readers. The ICC value generated between the 3 readers was 0.964, indicating that inter-reader variability was small, too. Subgroup analyses showed that both intra- and inter-reader variabilities were lower for larger than for smaller plaques. Mean CVs were similar for the 5S- and 10S-methods with a RC of 4.7 μl. The RC between both methods as well as the CVs were comparatively lower for larger plaques.</p> <p>Conclusion</p> <p>By implementing standardised central 3D US reading protocols and strict quality control procedures highly reliable ultrasonic re-readings of plaque images can be achieved in large multicentre trials.</p

Engineering Ising-XY spin models in a triangular lattice via tunable artificial gauge fields

Emulation of gauge fields for ultracold atoms provides access to a class of exotic states arising in strong magnetic fields. Here we report on the experimental realisation of tunable staggered gauge fields in a periodically driven triangular lattice. For maximal staggered magnetic fluxes, the doubly degenerate superfluid ground state breaks both a discrete Z2 (Ising) symmetry and a continuous U(1) symmetry. By measuring an Ising order parameter, we observe a thermally driven phase transition from an ordered antiferromagnetic to an unordered paramagnetic state and textbook-like magnetisation curves. Both the experimental and theoretical analysis of the coherence properties of the ultracold gas demonstrate the strong influence of the Z2 symmetry onto the condensed phase

Prediction of left lobe hypertrophy after right lobe radioembolization of the liver using a clinical data model with external validation

In cirrhotic patients with hepatocellular carcinoma (HCC), right-sided radioembolization (RE) with Yttrium-90-loaded microspheres is an established palliative therapy and can be considered a “curative intention” treatment when aiming for sequential tumor resection. To become surgical candidate, hypertrophy of the left liver lobe to > 40% (future liver remnant, FLR) is mandatory, which can develop after RE. The amount of radiation-induced shrinkage of the right lobe and compensatory hypertrophy of the left lobe is difficult for clinicians to predict. This study aimed to utilize machine learning to predict left lobe liver hypertrophy in patients with HCC and cirrhosis scheduled for right lobe RE, with external validation. The results revealed that machine learning can accurately predict relative and absolute volume changes of the left liver lobe after right lobe RE. This prediction algorithm could help to estimate the chances of conversion from palliative RE to curative major hepatectomy following significant FLR hypertrophy

Sensing dot with high output swing for scalable baseband readout of spin qubits

A key requirement for quantum computing, in particular for a scalable quantum computing architecture, is a fast and high-fidelity qubit readout. For semiconductor based qubits, one limiting factor is the output swing of the charge sensor. We demonstrate GaAs and Si/SiGe asymmetric sensing dots (ASDs), which exceed the response of a conventional charge sensing dot by more than ten times, resulting in a boosted output swing of $3\,\text{mV}$. This substantially improved output signal is due to a device design with a strongly decoupled drain reservoir from the sensor dot, mitigating negative feedback effects of conventional sensors. The large output signal eases the use of very low-power readout amplifiers in close proximity to the qubit and will thus render true scalable qubit architectures with semiconductor based qubits possible in the future.Comment: 8 pages, 7 figure

Tailoring potentials by simulation-aided design of gate layouts for spin qubit applications

Gate-layouts of spin qubit devices are commonly adapted from previous successful devices. As qubit numbers and the device complexity increase, modelling new device layouts and optimizing for yield and performance becomes necessary. Simulation tools from advanced semiconductor industry need to be adapted for smaller structure sizes and electron numbers. Here, we present a general approach for electrostatically modelling new spin qubit device layouts, considering gate voltages, heterostructures, reservoirs and an applied source-drain bias. Exemplified by a specific potential, we study the influence of each parameter. We verify our model by indirectly probing the potential landscape of two design implementations through transport measurements. We use the simulations to identify critical design areas and optimize for robustness with regard to influence and resolution limits of the fabrication process.Comment: 10 pages, 6 figure

Outcomes and Complication Rates of Cuff Downsizing in the Treatment of Worsening or Persistent Incontinence After Artificial Urinary Sphincter Implantation

Purpose This study investigated the functional outcomes and complication rates of cuff downsizing for the treatment of recurrent or persistent stress urinary incontinence (SUI) in men after the implantation of an artificial urinary sphincter (AUS). Methods Data from our institutional AUS database spanning the period from 2009 to 2020 were retrospectively analyzed. The number of pads per day was determined, a standardized quality of life (QoL) questionnaire and the International Consultation on Incontinence Questionnaire (ICIQ) were administered, and postoperative complications according to the Clavien-Dindo classification were analyzed. Results Out of 477 patients who received AUS implantation during the study period, 25 (5.2%) underwent cuff downsizing (median age, 77 years; interquartile range [IQR], 74–81 years; median follow-up, 4.4 years; IQR, 3–6.9 years). Before downsizing, SUI was very severe (ICIQ score 19–21) or severe (ICQ score 13–18) in 80% of patients, moderate (ICIQ score 6–12) in 12%, and slight (ICIQ score 1–5) in 8%. After downsizing, 52% showed an improvement of >5 out of 21 points. However, 28% still had very severe or severe SUI, 48% had moderate SUI, and 20% had slight SUI. One patient no longer had SUI. In 52% of patients, the use of pads per day was reduced by ≥50%. QoL improved by >2 out of 6 points in 56% of patients. Complications (infections/urethral erosions) requiring device explantation occurred in 36% of patients, with a median time to event of 14.5 months. Conclusions Although cuff downsizing carries a risk of AUS explantation, it can be a valuable treatment option for selected patients with persistent or recurrent SUI after AUS implantation. Over half of patients experienced improvements in symptoms, satisfaction, ICIQ scores, and pad use. It is important to inform patients about the potential risks and benefits of AUS to manage their expectations and assess individual risks