Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.

Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by the Mycobacterium TB bacteria, continues to pose a serious threat to world health. The TB diagnosis phase includes a patient's medical history, physical examination, chest X-rays, and laboratory procedures, such as molecular testing and sputum culture. In artificial intelligence (AI), machine learning (ML) is an advanced study of statistical algorithms that can learn from historical data and generalize the results to unseen data.

Autoimmune diseases and adverse pregnancy outcomes: an umbrella review.

Background: The prevalence of autoimmune conditions is two-fold higher in women than in men, especially during the reproductive years. Autoimmune conditions have been associated with a greater risk of adverse pregnancy outcomes, and some conditions have been studied more than others with inconsistent findings. The objective of this umbrella review was to identify, appraise, synthesise, and consolidate findings from published systematic reviews of autoimmune conditions and adverse pregnancy outcomes.

Hookworm infection induces glycometabolic modulation in South Indian individuals with type 2 diabetes.

Objectives: A number of epidemiological studies have demonstrated that there is an inverse relationship between helminth infections and diabetes mellitus, suggesting that helminth infection may have a positive effect on type 2 diabetes mellitus (T2DM). However, the association between hookworm infection and T2DM has barely been studied. Hence, we aimed to investigate and analyze the interaction and association between hookworm infection and T2DM.