Artificial Intelligence Medical Compendium

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Swallowing and speech impairments are common in Parkinson's disease (PD) and can significantly affect health and quality of life. Traditional methods for assessing and managing these functions rely on in-person visits and large, expensive equipment, ... read more 

Mixture cure rate models represent a valuable tool to delineate the presence of a cured subgroup in the entire population under study. Among the vast literature, a popular research line is to regress the probability of an individual being cured on co... read more 

PURPOSE: To assess the performance of artificial intelligence (AI) compared with physicians in detecting rotator cuff tear (RCT) on medical imaging and evaluating the ability of AI to predict outcomes after arthroscopic rotator cuff repair. METHODS: ... read more 

ObjectiveTo develop and compare models predicting which infants with cleft lip and/or palate (CL/P) will be underweight at 4 months, using multicenter electronic health record data.DesignUsing data from birth to 3 months, we evaluated 63 anthropometr... read more 

Artificial intelligence (AI) chatbots are increasingly explored as clinical decision support tools, but their accuracy and applicability remain insufficiently evaluated. We therefore evaluated and compared the accuracy, completeness, readability, and... read more 

PURPOSE: Artificial intelligence (AI) technologies have the potential to enhance the delivery of speech-language pathology services. One area of practice that could benefit from AI is automated screenings for developmental language disorder (DLD) in ... read more 

STUDY OBJECTIVES: Polysomnography (PSG) is the gold standard for diagnosing sleep disorders, which are recognized as cardiovascular risk factors. Single-lead electrocardiograms (ECGs) are recorded during PSG but rarely analyzed, presenting an opportu... read more 

PurposeLarge language models (LLMs) are increasingly used in clinical data workflows, but most clinicians lack the time, training, or support to build predictive models. We evaluated whether a ChatGPT-assisted workflow could enable clinicians to inde... read more 

Genotype-to-phenotype (G2P) prediction is the central mission of modern plant breeding. Genomic data accumulation has outpaced the ability of current frameworks to predict field performance across variable environments. Statistical genomic models del... read more