Predicting bone metastasis-free survival in non-small cell lung cancer from preoperative CT via deep learning.

Accurate prediction of bone metastasis-free survival (BMFS) after complete surgical resection in patients with non-small cell lung cancer (NSCLC) may facilitate appropriate follow-up planning. The aim of this study was to establish and validate a preoperative CT-based deep learning (DL) signature to predict BMFS in NSCLC patients. We performed a retrospective analysis of 1547 NSCLC patients who underwent complete surgical resection, followed by at least 36 months of monitoring at two hospitals.

Deep learning signature based on multiphase enhanced CT for bladder cancer recurrence prediction: a multi-center study.

Background: Accurate stratification of recurrence risk for bladder cancer (BCa) is essential for precise individualized therapy. This study aimed to develop and validate a model for predicting the risk of recurrence in BCa patients postoperatively using 3-phase enhanced CT images.

Methods: We retrospectively enrolled 874 BCa patients across four centers between January 2006 and December 2021.

Fault Diagnosis Method for Imbalanced Data Based on Multi-Signal Fusion and Improved Deep Convolution Generative Adversarial Network.

The realization of accurate fault diagnosis is crucial to ensure the normal operation of machines. At present, an intelligent fault diagnosis method based on deep learning has been widely applied in mechanical areas due to its strong ability of feature extraction and accurate identification. However, it often depends on enough training samples.

Comparison of optical quality and distinct macular thickness in femtosecond laser-assisted versus phacoemulsification cataract surgery.

Background: Optical quality and macular thickness changing optical quality is rarely reported after femtosecond laser-assisted cataract surgery (FLACS). In current research, we evaluated optical quality recovery and distinct macular thickness changes after FLACS and phacoemulsification cataract surgery (PCS).

Methods: A total of 100 cataract patients (100 eyes) were included (50 eyes for the FLACS group and 50 eyes for the PCS group).

Entropy Exchange and Thermodynamic Properties of the Single Ion Cooling Process.

A complete quantum cooling cycle may be a useful platform for studying quantum thermodynamics just as the quantum heat engine does. Entropy change is an important feature which can help us to investigate the thermodynamic properties of the single ion cooling process. Here, we analyze the entropy change of the ion and laser field in the single ion cooling cycle by generalizing the idea in Reference ( , , 043002) to a single ion system.