Robust diabetic prediction using ensemble machine learning models with synthetic minority over-sampling technique.

This paper addresses the pressing issue of diabetes, which is a widespread condition affecting a huge population worldwide. As cells become less responsive to insulin or fail to produce it adequately, blood sugar levels rise. This has the potential to cause severe health complications including kidney disease, vision impairment and heart conditions.

A Pleiotropic Nanomedicine Mitigates Splenic Hyperplasia, Ineffective Erythropoiesis, G6PDH Anomaly through Redox Buffering in Preclinical Mice Model.

Here, we present a pleiotropic nanomedicine-a smart, functionalized redox buffering nanoparticle-that may be used to treat hematological diseases, associated splenic hyperplasia, and issues related to restricted erythropoiesis. With a diameter of 5-7 nm, the spherical nanomaterial is made of manganese oxide and citrate. Here, we have produced the novel nanomaterial and, using cutting-edge electron microscopic and spectroscopic techniques, extensively assessed its redox buffering potential in vitro with its structural integrity.

Pneumonia detection on chest X-rays from Xception-based transfer learning and logistic regression.

Pneumonia is a dangerous disease that kills millions of children and elderly patients worldwide every year. The detection of pneumonia from a chest x-ray is perpetrated by expert radiologists. The chest x-ray is cheaper and is most often used to diagnose pneumonia.