Yixin Yang

TL;DR: A greater number of ELNs is associated with more-accurate node staging and better long-term survival of resected NSCLC and is recommended as the cut point for evaluating the quality of LN examination or prognostic stratification postoperatively for patients with declared node-negative disease.

TL;DR: A comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data is provided.

TL;DR: The PSOSAHT algorithm framework proposed previously is adapted, where particle swarm optimization based exploration and simulated annealing based exploitation are well integrated, and the hypothesis test is to compare the stochastic makespan in statistical sense to avoid repeated search.

TL;DR: An effective scatter search based memetic algorithm (SS-MA) is proposed to address the difficulties of proposed DAPFSP-T model and could yield satisfactory searching performances, where solutions are significantly improved compared with multiple heuristic methods.

TL;DR: A new type of distributed permutation flow-shop scheduling problem (DPFSP) is proposed, in which different transport timetable and different loading capacity for each factory are considered, which is the first report on incorporating vehicle timetables and vehicle capacities to DPFSP.