GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints

The number of information systems (IS) studies dealing with explainable artificial intelligence (XAI) is currently exploding as the field demands more transparency about the internal decision logic of machine learning (ML) models. However, most techniques subsumed under XAI provide post-hoc-analytical explanations, which have to be considered with caution as they only use approximations of the underlying ML model. Therefore, our paper investigates a series of intrinsically interpretable ML models and discusses their suitability for the IS community. More specifically, our focus is on advanced extensions of generalized additive models (GAM) in which predictors are modeled independently in a non-linear way to generate shape functions that can capture arbitrary patterns but remain fully interpretable. In our study, we evaluate the prediction qualities of five GAMs as compared to six traditional ML models and assess their visual outputs for model interpretability. On this basis, we investigate their merits and limitations and derive design implications for further improvements

Europium cyclooctatetraene nanowire carpets: A low-dimensional, organometallic, and ferromagnetic insulator

We investigate the magnetic and electronic properties of europium cyclooctatetraene (EuCot) nanowires by means of low-temperature X-ray magnetic circular dichroism (XMCD) and scanning tunneling microscopy (STM) and spectroscopy (STS). The EuCot nanowires are prepared in situ on a graphene surface. STS measurements identify EuCot as an insulator with a minority band gap of 2.3 eV. By means of Eu M5,4 edge XMCD, orbital and spin magnetic moments of (−0.1 ± 0.3)μB and (+7.0 ± 0.6)μB, respectively, were determined. Field-dependent measurements of the XMCD signal at the Eu M5 edge show hysteresis for grazing X-ray incidence at 5 K, thus confirming EuCot as a ferromagnetic material. Our density functional theory calculations reproduce the experimentally observed minority band gap. Modeling the experimental results theoretically, we find that the effective interatomic exchange interaction between Eu atoms is on the order of millielectronvolts, that magnetocrystalline anisotropy energy is roughly half as big, and that dipolar energy is approximately ten times lower

A Light in the Dark: Deep Learning Practices for Industrial Computer Vision

In recent years, large pre-trained deep neural networks (DNNs) have revolutionized the field of computer vision (CV). Although these DNNs have been shown to be very well suited for general image recognition tasks, application in industry is often precluded for three reasons: 1) large pre-trained DNNs are built on hundreds of millions of parameters, making deployment on many devices impossible, 2) the underlying dataset for pre-training consists of general objects, while industrial cases often consist of very specific objects, such as structures on solar wafers, 3) potentially biased pre-trained DNNs raise legal issues for companies. As a remedy, we study neural networks for CV that we train from scratch. For this purpose, we use a real-world case from a solar wafer manufacturer. We find that our neural networks achieve similar performances as pre-trained DNNs, even though they consist of far fewer parameters and do not rely on third-party datasets

Microfluidics/CMOS orthogonal capabilities for cell biology

The study of individual cells and cellular networks can greatly benefit from the capabilities of microfabricated devices for the stimulation and the recording of electrical cellular events. In this contribution, we describe the development of a device, which combines capabilities for both electrical and pharmacological cell stimulation, and the subsequent recording of electrical cellular activity. The device combines the unique advantages of integrated circuitry (CMOS technology) for signal processing and microfluidics for drug delivery. Both techniques are ideally suited to study electrogenic mammalian cells, because feature sizes are of the same order as the cell diameter, ∼ 50 μm. Despite these attractive features, we observe a size mismatch between microfluidic devices, with bulky fluidic connections to the outside world, and highly miniaturized CMOS chips. To overcome this problem, we developed a microfluidic flow cell that accommodates a small CMOS chip. We simulated the performances of a flow cell based on a 3-D microfluidic system, and then fabricated the device to experimentally verify the nutrient delivery and localized drug delivery performance. The flow-cell has a constant nutrient flow, and six drug inlets that can individually deliver a drug to the cells. The experimental analysis of the nutrient and drug flow mass transfer properties in the flowcell are in good agreement with our simulations. For an experimental proof-of-principle, we successfully delivered, in a spatially resolved manner, a ‘drug' to a culture of HL-1 cardiac myocyte

Janus kinase 2 inhibition by pacritinib as potential therapeutic target for liver fibrosis

anus kinase 2 (JAK2) signaling is increased in human and experimental liver fibrosis with portal hypertension. JAK2 inhibitors, such as pacritinib, are already in advanced clinical development for other indications and might also be effective in liver fibrosis. Here, we investigated the antifibrotic role of the JAK2 inhibitor pacritinib on activated hepatic stellate cells (HSCs) in vitro and in two animal models of liver fibrosis in vivo.Jonel Trebicka is supported by the German Research Foundation project ID 403224013–SFB 1382 (A09); by the German Federal Ministry of Education and Research (BMBF) for the DEEP‐HCC project; by the Hessian Ministry of Higher Education, Research, and the Arts (HMWK) for the ENABLE cluster project; and by Eurostars (Grant ID 12350). The MICROB‐PREDICT (project ID 825694), DECISION (project ID 847949), GALAXY (project ID 668031), LIVERHOPE (project ID 731875), and IHMCSA (project ID 964590) projects have received funding from the European Union's Horizon 2020 research and innovation program. The manuscript reflects only the authors' views, and the European Commission is not responsible for any use that may be made of the information it contains. The funders had no influence on study design, data collection and analysis, decision to publish, or preparation of the manuscript

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised