Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection ar

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Ten years of lung transplantation in Switzerland: results of the Swiss Lung Transplant Registry.

Lung transplantation has evolved from an experimental procedure to a viable therapeutic option in many countries. In Switzerland, the first lung transplant was performed in November 1992, more than ten years after the first successful procedure world-wide. Thenceforward, a prospective national lung transplant registry was established, principally to enable quality control. The data of all patients transplanted in the two Swiss Lung Transplant centres Zurich University Hospital and Centre de Romandie (Geneva-Lausanne) were analysed. In 10 years 242 lung transplants have been performed. Underlying lung diseases were cystic fibrosis including bronchiectasis (32%), emphysema (32%), parenchymal disorders (19%), pulmonary hypertension (11%) and lymphangioleiomyomatosis (3%). There were only 3% redo procedures. The 1, 5 and 9 year survival rates were 77% (95% CI 72-82), 64% (95% CI 57-71) and 56% (95% CI 45-67), respectively. The 5 year survival rate of patients transplanted since 1998 was 72% (95% CI 64-80). Multivariate Cox regression analysis revealed that survival was significantly better in this group compared to those transplanted before 1998 (HR 0.44, 0.26-0.75). Patients aged 60 years and older (HR 5.67, 95% CI 2.50-12.89) and those with pulmonary hypertension (HR 2.01, 95% CI 1.10-3.65) had a significantly worse prognosis The most frequent causes of death were infections (29%), bronchiolitis obliterans syndrome (25%) and multiple organ failure (14%). The 10-year Swiss experience of lung transplantation compares favourably with the international data. The best results are obtained in cystic fibrosis, pulmonary emphysema and parenchymal disorders

VIRTUAL-ME: A Library for Smart Autonomous Agents in Multiple Virtual Environments

Emulating human behaviour is a very desirable characteristic for virtual agents. There is plenty of literature that focuses on a single specific aspect of human behaviour emulation, but it is quite rare to find a collection of implementations encompassing several aspects of the problem. In this work we present VIRTUAL-ME (VIRTUal Agent Library for Multiple Environment), a library that provides programmers with a complete set of classes that assembles various human characteristics and makes it possible to build smart agents. The assessment of the library capabilities to populate a generic virtual environment is also discussed through the analysis of different case studies

Probucol inhibits in-stent thrombosis and neointimal hyperplasia by promoting re-endothelialization

BACKGROUND: Evidence suggests that delayed re-endothelialization is responsible for in-stent thrombosis. Probucol inhibits neointimal thickening in animals via enhanced re-endothelialization and is the only oral drug that consistently inhibits restenosis after coronary angioplasty in humans. Here, we examined the effects of probucol on re-endothelialization and neointimal formation in a stent model. METHODS AND RESULTS: New Zealand White rabbits were fed a hypercholesterolemic diet with probucol (1%) or without (control) (n=11 each) for 6 weeks. At 2 weeks, endothelial denudation and stenting of the iliac artery was performed. Iliac arteries were harvested at week 6, and stented segments sectioned and analyzed. Compared with control, probucol increased in-stent re-endothelialization (74+/-6% in controls versus 93+/-3% in probucol-treated; P=0.008), and decreased average luminal stenosis (58+/-27 versus 31+/-16%; P=0.01) and stent depth (619+/-310 versus 314+/-158mum; P=0.009). Compared with control, probucol also decreased accumulation of macrophages in the neointima. Furthermore, none of the probucol-treated rabbits had in-stent thrombosis, whereas four of eleven control rabbits showed thrombosis (P=0.04). CONCLUSIONS: Probucol demonstrates anti-restenotic and appears to have anti-thrombotic properties that are likely related to its ability to promote in-stent re-endothelialization