Artificial Intelligence Medical Compendium

A central challenge in molecular magnetism is achieving scalable magnetic moments as molecular systems increase in size. Phenalenyl, a stable radical with an S = 1/2 spin state, serves as an appealing building block for molecular magnetic materials. ... read more 

In response to the need for biotic monitoring of petroleum hydrocarbon contamination in Antarctica, we applied machine learning (ML) techniques to classify polycyclic aromatic hydrocarbon contamination in Nacella concinna. Concentrations of 16 priori... read more 

High-resolution Computed Tomography (CT) is the gold standard medical imaging technique for bone assessment. However, its clinical use is limited by high radiation dose (8.8 mSv; biplanar X-rays 1.4 mSv), cost, and reduced accessibility. These barrie... read more 

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BACKGROUND: Meningiomas are the most common dural-based intracranial tumors, yet Indian literature is predominantly composed of limited single-center studies, restricting nationwide representation and data-driven decision making. With artificial inte... read more 

As artificial intelligence (AI) rapidly integrates into higher education, AI tools are increasingly being utilized to support student learning. Although these tools offer efficiency and convenience, their psychological implications-particularly vis-à... read more 

BACKGROUND: Child neglect and abuse are prevalent worldwide yet often incompletely reported and are frequently associated with long-term adverse physical and mental health outcomes. Municipal-level administrative data contain indicators relevant to d... read more 

Paclitaxel, a clinically potent anticancer drug derived from Taxus species, faces persistent challenges in sustainable supply. Synthetic biology presents substantial opportunities for its de novo production, particularly with recent breakthroughs in ... read more 

BACKGROUND: Chronic postsurgical pain is a significant medical concern, particularly in cancer patients. However, most previous studies overlooked the psychological mechanisms contributing to this risk. The present study aimed to identify baseline pr... read more 

EEG recordings obtained before medication are regarded as valuable biological indicators for depression detection. Currently, depression diagnosis based on EEG using convolutional neural networks (CNNs) has achieved relatively high detection performa... read more