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To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passing the remaining examinations to standard reporting.

A dataset of 400 CXRs including 200 difficult lung cancer cases was curated. Examinations were reviewed by three FRCR radiologists and an AI algorithm to establish performance in tumour identification. AI and radiologist labels were combined retrospectively to simulate the proposed AI triage workflow.

When used as a standalone algorithm, AI classification was equivalent to the average radiologist performance. The best overall performances were achieved when AI was combined with radiologists, with an average reduction of missed cancers of 60%. Combination with AI also standardised the performance of radiologists. The greatest improvements were observed when common sources of errors were present, such as distracting findings.

The proposed AI implementation pathway stands to reduce radiologist errors and improve clinician reporting performance. Furthermore, taking a radiologist-centric approach in the development of clinical AI holds promise for catching systematically missed lung cancers. This represents a tremendous opportunity to improve patient outcomes for lung cancer diagnosis.

The proposed AI implementation pathway stands to reduce radiologist errors and improve clinician reporting performance. Furthermore, taking a radiologist-centric approach in the development of clinical AI holds promise for catching systematically missed lung cancers. This represents a tremendous opportunity to improve patient outcomes for lung cancer diagnosis.

Biliary stricture (BS) is a severe complication after liver transplantation. It is difficult to treat, especially after living donor liver transplantation (LDLT). click here We successfully treated 4 patients for intractable BS after LDLT. All patients had developed cholangitis with stenosis of bile ducts anastomosis. CASE 1 . A 65-year-old woman underwent LDLT with right lobe graft and duct-to-duct biliary reconstruction. Internal plastic stents inserted by endoscopic retrograde cholangiography (ERC) were changed quarterly for the next 2 years. CASE 2 A 55-year-old man underwent LDLT with right lobe graft and duct-to-duct biliary reconstruction. Insertion of internal plastic stents by ERC was attempted; however, the posterior bile duct branch showed complete obstruction. After percutaneous transhepatic biliary drainage (PTCD), the stents were inserted using the rendezvous technique of ERC and were changed by ERC quarterly for the next 3 years. CASE 3 A 22-year-old man underwent LDLT with left lobe graft and hepaticojejunostomy. An external drainage tube was inserted by PTCD, and stents were changed quarterly for the next 2 years. CASE 4 A 60-year-old man underwent LDLT with right lobe graft and hepaticojejunostomy. An external drainage tube was inserted by PTCD, and changed to a metallic stent after 1 year. Three months later the stent was extracted using the rendezvous technique of double balloon enteroscopy.

BS of complete obstruction type after LDLT is difficult to treat. Appropriate procedures should be chosen based on the types of strictures and biliary reconstruction methods.

BS of complete obstruction type after LDLT is difficult to treat. Appropriate procedures should be chosen based on the types of strictures and biliary reconstruction methods.In this study, an asynchronous H∞ state feedback controller is devised for Markov jump discrete-time systems (MJDTSs) with time-varying delay. "Asynchronous" means that the system switching mode θk, the controller mode ϑk and the quantizer mode λk are different from each other. The first one is homogeneous and the last two are non-homogeneous. In particular, as a promotion of existing work, we firstly attempt to propose the transition probabilities (TPs) of the three Markov chains (MCs) are not completely known. In addition, the discrete time-varying delay and its infinitely distributed ones are considered. Moreover, according to the Lyapunov stability theory and stochastic process, it is established for the sufficient criterion to ensure the stochastic stability of resulting closed-loop MJDTSs with an H∞ attenuation performance index. The feasibility and effectiveness of the proposed method are validated by three examples.In this paper, a fixed-time controller under the mechanism of event-trigger is designed for a class of nonlinear pure-feedback systems with non-differentiable non-affine functions. By properly modeling non-affine terms, the limitation of the partial derivatives of non-affine functions is eliminated. In our design process, we first develop a fixed-time adaptive controller using decoupling method. Then, a relative threshold event-trigger mechanism (ETM) is introduced in Section 3.1. The proposed controller can not only stabilize the system within a fixed-time, but also save communication resources more effectively. Lastly, the feasibility of the proposed control scheme is verified by two simulation examples.The reliability prediction of gearbox is a complex and challenging topic. The purpose of this research is to propose a hybrid difference iterative forecasting model to forecast reliability of the gearbox. On this score, a hybrid model based on the fractional Lévy stable motion (fLsm), the Grey Model (GM) and the metabolism method is proposed. To solve the problem of insensitivity to weak faults inside the gearbox, we use feature extraction method to reveal the gearbox degradation. Then, the least square theory is used to separate the degradation sequence in the gearbox into a deterministic term with monotonicity and a stochastic term with Long-Range Dependence (LRD). Next, the fLsm with LRD and non-Gaussian is used to forecast the stochastic term, the deterministic term is simulated by the GM, and the hybrid forecasting model is used to modify the prediction results. The metabolism method is used to update the degradation sequence and to forecast longer-term trend. Finally, a case demonstrated that superiority and generality of the hybrid forecasting model.