Artificial Intelligence Medical Compendium

Effluents generated in the food and beverage industry typically contain elevated concentrations of organic carbon sources and inorganic nutrients, representing a significant environmental burden as global food demand continues to rise. Owing to their... read more 

Point-of-care ultrasound (POCUS) in obstetrics and gynecology has evolved from a pragmatic bedside adjunct into a rapidly expanding clinical, educational and technological field. Since the publication of earlier narrative reviews, the discipline has ... read more 

Bone defects continue to pose a significant challenge in orthopedic and reconstructive surgery, especially when presenting as large, irregular, infected, or load-bearing lesions. The advent of three-dimensional (3D) printing has opened new avenues fo... read more 

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The integration of artificial intelligence (AI) into digital media and health information ecosystems-including large language model chatbots, AI-enabled mHealth applications, and algorithmically curated social media-is reshaping how adolescents encou... read more 

OBJECTIVES: Cross-border care, teleradiology, and international referral pathways increasingly require radiology report translation, but isolated mistranslations may alter clinical meaning. We evaluated German-to-English machine translation of radiol... read more 

Accurate estimation of above-ground biomass (AGB) is essential for sustainable forest resource management and carbon stock assessment. This study focuses on the Pembi Forest, Telangana, India, where synthetic aperture radar (SAR) data from ALOS-2 PAL... read more 

BACKGROUND: Raised intracranial pressure is one of the most severe secondary insults after traumatic brain injury. Recognising physiological patterns before they progress to dangerous intracranial pressure elevations could enable preventive rather th... read more 

Artificial neural network (ANN) techniques have emerged as powerful data-driven tools for their effectiveness in analysis, modeling, and simulation. These supervised learning approaches are designed to reduce the error between predicted and observed ... read more 

OBJECTIVE: This study aims to evaluate the efficacy of integrating pre-radiotherapy and mid-radiotherapy radiomics, temporal changes in tumor radiomics (delta radiomics) during chemoradiotherapy, and clinical variables into prognostic models for indi... read more