Redefining retinal vessel segmentation: empowering advanced fundus image analysis with the potential of GANs.

Retinal vessel segmentation is a critical task in fundus image analysis, providing essential insights for diagnosing various retinal diseases. In recent years, deep learning (DL) techniques, particularly Generative Adversarial Networks (GANs), have garnered significant attention for their potential to enhance medical image analysis. This paper presents a novel approach for retinal vessel segmentation by harnessing the capabilities of GANs.

The BCPM method: decoding breast cancer with machine learning.

Breast cancer prediction and diagnosis are critical for timely and effective treatment, significantly impacting patient outcomes. Machine learning algorithms have become powerful tools for improving the prediction and diagnosis of breast cancer. The Breast Cancer Prediction and Diagnosis Model (BCPM), which utilises machine learning techniques to improve the precision and efficiency of breast cancer diagnosis and prediction, is presented in this paper.

Loss of engagement in controlling chronic anticoagulation therapy during Covid-19 stringency measures. A single center experience of disproportioned increase of stuck mechanical valves.

Stuck valve is a very rare and severe complication that occurs in mechanical valve replacement patients with ineffective anticoagulation. However, with COVID-19 restriction measures, it became challenging to regularly assess INR to make sure it falls within the target therapeutic range to prevent this complication. We present a series of 10 patients who either underwent transthoracic echocardiography for a suspected stuck valve or were seen at the outpatient valve clinic with the residual consequences of a stuck valve during the COVID-19 restriction measures in our institute.