COOD:Combined out-of-distribution detection using multiple measures for anomaly & novel class detection in large-scale hierarchical classification

High-performing out-of-distribution (OOD) detection, both anomaly and novel class, is an important prerequisite for the practical use of classification models. In this paper, we focus on the species recognition task in images concerned with large databases, a large number of fine-grained hierarchical classes, severe class imbalance, and varying image quality. We propose a framework for combining individual OOD measures into one combined OOD (COOD) measure using a supervised model. The individual measures are several existing state-of-the-art measures and several novel OOD measures developed with novel class detection and hierarchical class structure in mind. COOD was extensively evaluated on three large-scale (500k+ images) biodiversity datasets in the context of anomaly and novel class detection. We show that COOD outperforms individual, including state-of-the-art, OOD measures by a large margin in terms of TPR@1% FPR in the majority of experiments, e.g., improving detecting ImageNet images (OOD) from 54.3% to 85.4% for the iNaturalist 2018 dataset. SHAP (feature contribution) analysis shows that different individual OOD measures are essential for various tasks, indicating that multiple OOD measures and combinations are needed to generalize. Additionally, we show that explicitly considering ID images that are incorrectly classified for the original (species) recognition task is important for constructing high-performing OOD detection methods and for practical applicability. The framework can easily be extended or adapted to other tasks and media modalities

Antibacterial Envelope to Prevent Cardiac Implantable Device Infection

Background Infections after placement of cardiac implantable electronic devices (CIEDs) are associated with substantial morbidity and mortality. There is limited evidence on prophylactic strategies, other than the use of preoperative antibiotics, to prevent such infections. Methods We conducted a randomized, controlled clinical trial to assess the safety and efficacy of an absorbable, antibiotic-eluting envelope in reducing the incidence of infection associated with CIED implantations. Patients who were undergoing a CIED pocket revision, generator replacement, or system upgrade or an initial implantation of a cardiac resynchronization therapy defibrillator were randomly assigned, in a 1:1 ratio, to receive the envelope or not. Standard-of-care strategies to prevent infection were used in all patients. The primary end point was infection resulting in system extraction or revision, long-term antibiotic therapy with infection recurrence, or death, within 12 months after the CIED implantation procedure. The secondary end point for safety was procedure-related or system-related complications within 12 months. Results A total of 6983 patients underwent randomization: 3495 to the envelope group and 3488 to the control group. The primary end point occurred in 25 patients in the envelope group and 42 patients in the control group (12-month Kaplan-Meier estimated event rate, 0.7% and 1.2%, respectively; hazard ratio, 0.60; 95% confidence interval [CI], 0.36 to 0.98; P=0.04). The safety end point occurred in 201 patients in the envelope group and 236 patients in the control group (12-month Kaplan-Meier estimated event rate, 6.0% and 6.9%, respectively; hazard ratio, 0.87; 95% CI, 0.72 to 1.06; P<0.001 for noninferiority). The mean (+/- SD) duration of follow-up was 20.7 +/- 8.5 months. Major CIED-related infections through the entire follow-up period occurred in 32 patients in the envelope group and 51 patients in the control group (hazard ratio, 0.63; 95% CI, 0.40 to 0.98). Conclusions Adjunctive use of an antibacterial envelope resulted in a significantly lower incidence of major CIED infections than standard-of-care infection-prevention strategies alone, without a higher incidence of complications