Big data analytics and machine learning in hematology: Transformative insights, applications and challenges.

The integration of big data analytics and machine learning (ML) into hematology has ushered in a new era of precision medicine, offering transformative insights into disease management. By leveraging vast and diverse datasets, including genomic profiles, clinical laboratory results, and imaging data, these technologies enhance diagnostic accuracy, enable robust prognostic modeling, and support personalized therapeutic interventions. Advanced ML algorithms, such as neural networks and ensemble learning, facilitate the discovery of novel biomarkers and refine risk stratification for hematological disorders, including leukemias, lymphomas, and coagulopathies.

The role of pharmacological interventions in managing urological complications during pregnancy and childbirth: A review.

Pregnancy leads to a number of structural and functional changes in the urinary system, which makes females susceptible to urological complications. This review aims to discuss the epidemiology, complications and prevention and management of urinary tract infections (UTIs), kidney stones and bladder dysfunction in pregnancy. UTIs are the most common urological problem presenting in 10% of pregnant women; Escherichia coli is the most common causative organism.