Background Although agricultural health has gained importance, to date, much of the
existing research relies on traditional epidemiological approaches that often face limitations …

Deep learning techniques like neural networks show promise for extracting insights from
electronic health records (EHRs) to enhance clinical decision-making and improve patient …

Objective The study aims to identify distinct population-specific comorbidity progression
patterns, timely detect potential comorbidities, and gain better understanding of the …

Background Mycetoma is a serious, neglected tropical disease affecting the underprivileged
populations in resource-constrained communities of the rural tropical and subtropical …

Artificial Intelligence (AI) is transforming various industries by developing algorithms that
harness big data to improve efficiency, boost productivity, reduce costs and enhance the …

Background Vitamin D deficiency is strongly associated with the development of several
diseases. In the current context of a global pandemic of vitamin D deficiency, it is critical to …

Objective Empathy between doctors and patients is crucial in enhancing patient satisfaction
with medical consultations. This study, grounded in empathy theory, employs natural …

This research aimed to identify the principal factors predicting social welfare and inequality
in the neighbourhoods of Madrid city. A comprehensive dataset representing various …

The growing accessibility of extensive healthcare datasets has highlighted the need for solid
methods for discovering significant connections and trends that can guide clinical decision …

Despite significant advancements, lung cancer remains a formidable global health
challenge, necessitating effective diagnostic and prognostic methodologies. This survey …