Novel Hybrid Quantum Architecture-Based Lung Cancer Detection Using Chest Radiograph and Computerized Tomography Images.

Lung cancer, the second most common type of cancer worldwide, presents significant health challenges. Detecting this disease early is essential for improving patient outcomes and simplifying treatment. In this study, we propose a hybrid framework that combines deep learning (DL) with quantum computing to enhance the accuracy of lung cancer detection using chest radiographs (CXR) and computerized tomography (CT) images.

Replacing protein via enteral nutrition in a stepwise approach in critically ill patients: the REPLENISH randomized clinical trial protocol.

Background: Protein intake is recommended in critically ill patients to mitigate the negative effects of critical illness-induced catabolism and muscle wasting. However, the optimal dose of enteral protein remains unknown. We hypothesize that supplemental enteral protein (1.

Brinjal leaf diseases detection based on discrete Shearlet transform and Deep Convolutional Neural Network.

Different diseases are observed in vegetables, fruits, cereals, and commercial crops by farmers and agricultural experts. Nonetheless, this evaluation process is time-consuming, and initial symptoms are primarily visible at microscopic levels, limiting the possibility of an accurate diagnosis. This paper proposes an innovative method for identifying and classifying infected brinjal leaves using Deep Convolutional Neural Networks (DCNN) and Radial Basis Feed Forward Neural Networks (RBFNN).

Liberation From Mechanical Ventilation Before Decannulation From Venovenous Extracorporeal Life Support in Severe COVID-19 Acute Respiratory Distress Syndrome.

The coronavirus disease 2019 (COVID-19) pandemic has been associated with the significant use of venovenous extracorporeal membrane oxygenation (VVECMO) globally. Identifying strategies to optimize care is essential to improving patient important outcomes. By liberation from mechanical ventilation (MV) before VVECMO to provide awake-ECMO, complications related to MV could be minimized, leading to improved outcomes.