Artificial Intelligence Medical Compendium

Against the backdrop of China's new urbanization and regional coordination strategies, the social integration of rural-to-urban migrants has become an increasingly critical indicator of state governance modernization and institutional performance. Co... read more 

INTRODUCTION: Assessment of clinical performance has traditionally been a numbers game based upon Likert scale ratings. But, thanks to advances in the science of natural language processing (NLP), it is now possible to incorporate rich narrative data... read more 

PURPOSE: In this short communication, we consider the need for explainable AI from the perspective of a large multi-disciplinary research project for predicting cachexia in cancer patients. MATERIALS AND METHODS: In a series of meetings, comprising e... read more 

Aberrant sensori-/psychomotor functioning-including muscular hand weakness, sedentary behavior, psychomotor agitation, slowing, agitation, apathy, and anxiety-is increasingly recognized as a transdiagnostic feature across mental and neurodegenerative... read more 

With the aging population in Europe, particularly Hungary, unhealthy aging is emerging as a growing public health challenge. Physical inactivity is a modifiable risk factor for age-related diseases and remains highly prevalent. Increasing daily physi... read more 

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UNLABELLED: Bowel injuries following blunt abdominal trauma (BAT) are evasive to detect clinically and with current imaging modalities. These injuries require immediate recognition and operative intervention. Short diagnostic delays can result in sig... read more 

BACKGROUND: Axillary lymph node (ALN) burden is a key prognostic determinant in breast cancer and plays an important role in diagnosis and treatment planning. The noninvasive assessment of ALN burden might improve patient stratification and guide ind... read more 

Human and veterinary healthcare systems face many parallel challenges, yet opportunities for cross-sectoral learning remain underexplored. This scoping review aimed to compare healthcare delivery in both domains, highlighting operational inefficienci... read more 

This study applied decision-tree (DT) machine learning models to determine whether this approach is more accurate when classifying slip outcome during walking, and to refine the cutoff thresholds of each slip type. Kinematic data of the heel were col... read more