Predictive model for intraoperative decision-making in video-assisted thoracoscopic lobectomy: optimizing chest drain placement for high-risk patients.

Background: For years, it has been the common and widely accepted practice in thoracic surgery to place apical and basal drains after a lobectomy to completely drain the pleural cavity. With the development of thoracoscopic technology, it became apparent that the use of a single chest tube provided the same clinical results. However, sometimes tension pneumothorax occurs with the need for additional pleural drainage.

Surgical intervention for lung cancer in patients aged 75 and above: potential associations with increased mortality rates-a single-center observational study.

Background: Lung cancer, which is diagnosed two to three times more frequently in patients over the age of 70, is a leading cause of cancer-specific mortality. Given the elevated risk of morbidity and mortality, surgical intervention may not always be the most appropriate primary treatment option. This study aims to evaluate specific risk factors associated with postoperative morbidity and mortality in elderly patients and to optimize patient selection therefore improving surgical outcomes.

[Predictive model for additional intraoperative placement of chest drainage after thoracoscopic lobectomy].

Objective: To create a prognostic model determining the risk of tension pneumothorax and the need for intraoperative installation of additional drainage after thoracoscopic lobectomy.

Material And Methods: A retrospective multiple-center study included patients who underwent thoracoscopic lobectomy for lung cancer between 2016 and 2022. One drainage tube was used after surgery in all cases.

Deep reinforcement learning with significant multiplications inference.

We propose a sparse computation method for optimizing the inference of neural networks in reinforcement learning (RL) tasks. Motivated by the processing abilities of the brain, this method combines simple neural network pruning with a delta-network algorithm to account for the input data correlations. The former mimics neuroplasticity by eliminating inefficient connections; the latter makes it possible to update neuron states only when their changes exceed a certain threshold.

Sustainable Elastomers for Actuators: "Green" Synthetic Approaches and Material Properties.

Elastomeric materials have great application potential in actuator design and soft robot development. The most common elastomers used for these purposes are polyurethanes, silicones, and acrylic elastomers due to their outstanding physical, mechanical, and electrical properties. Currently, these types of polymers are produced by traditional synthetic methods, which may be harmful to the environment and hazardous to human health.