Lubricating Medical Devices with Fullerene-Like Nanoparticles

In the present work, MoS₂ nanoparticles with fullerene-like structure, and most particularly those doped with minute amounts of rhenium atoms, are used as additive to medical gels in order to facilitate their entry into constricted openings of soft material rings. This procedure is used to mimic the entry of endoscopes to constricted openings of the human body, like urethra, etc. It is shown that the Re-doped nanoparticles reduce the traction force used to retrieve the metallic lead of the endoscope from the soft ring by a factor close to three times with respect to the original gel. The mechanism of the mitigation of both friction and adhesion forces in these systems by the nanoparticles is discussed.     

A deep learning approach for classification of COVID and pneumonia using DenseNet-201

In the present paper, our model consists of deep learning approach: DenseNet201 for detection of COVID and Pneumonia using the Chest X-ray Images. The model is a framework consisting of the modeling software which assists in Health Insurance Portability and Accountability Act Compliance which protects and secures the Protected Health Information . The need of the proposed framework in medical facilities shall give the feedback to the radiologist for detecting COVID and pneumonia though the transfer learning methods. A Graphical User Interface tool allows the technician to upload the chest X-ray Image. The software then uploads chest X-ray radiograph (CXR) to the developed detection model for the detection. Once the radiographs are processed, the radiologist shall receive the Classification of the disease which further aids them to verify the similar CXR Images and draw the conclusion. Our model consists of the dataset from Kaggle and if we observe the results, we get an accuracy of 99.1%, sensitivity of 98.5%, and specificity of 98.95%. The proposed Bio-Medical Innovation is a user-ready framework which assists the medical providers in providing the patients with the best-suited medication regimen by looking into the previous CXR Images and confirming the results. There is a motivation to design more such applications for Medical Image Analysis in the future to serve the community and improve the patient care.