AIMC Topic: Humans

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Constitutive neural networks for main pulmonary arteries: discovering the undiscovered.

Biomechanics and modeling in mechanobiology
Accurate modeling of cardiovascular tissues is crucial for understanding and predicting their behavior in various physiological and pathological conditions. In this study, we specifically focus on the pulmonary artery in the context of the Ross proce...

Generative Artificial Intelligence and Misinformation Acceptance: An Experimental Test of the Effect of Forewarning About Artificial Intelligence Hallucination.

Cyberpsychology, behavior and social networking
Generative artificial intelligence (AI) tools could create statements that are seemingly plausible but factually incorrect. This is referred to as AI hallucination, which can contribute to the generation and dissemination of misinformation. Thus, the...

Deep transfer learning radiomics for distinguishing sinonasal malignancies: a preliminary MRI study.

Future oncology (London, England)
PURPOSE: This study aimed to assess the diagnostic accuracy of combining MRI hand-crafted (HC) radiomics features with deep transfer learning (DTL) in identifying sinonasal squamous cell carcinoma (SCC), adenoid cystic carcinoma (ACC), and non-Hodgki...

Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association.

Circulation. Genomic and precision medicine
Artificial intelligence is poised to transform cardio-oncology by enabling personalized care for patients with cancer, who are at a heightened risk of cardiovascular disease due to both the disease and its treatments. The rising prevalence of cancer ...

Utilization and perception of generative artificial intelligence by medical students in residency applications.

Journal of investigative medicine : the official publication of the American Federation for Clinical Research
After completing medical school in the United States, most students apply to residency programs to progress in their training. The residency application process contains numerous writing sections, including the personal statement, curriculum vitae, a...

Deep learning to quantify the pace of brain aging in relation to neurocognitive changes.

Proceedings of the National Academy of Sciences of the United States of America
Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes cumulative neuroanatomic aging since bi...

Label-Free Detection of Biochemical Changes during Cortical Organoid Maturation via Raman Spectroscopy and Machine Learning.

Analytical chemistry
Human cerebral organoids have become valuable tools in neurodevelopment research, holding promise for investigating neurological diseases and reducing drug development costs. However, clinical translation and large-scale production of brain organoids...

Natural Language Processing Methods for the Study of Protein-Ligand Interactions.

Journal of chemical information and modeling
Natural Language Processing (NLP) has revolutionized the way computers are used to study and interact with human languages and is increasingly influential in the study of protein and ligand binding, which is critical for drug discovery and developmen...

Inductive reasoning with large language models: A simulated randomized controlled trial for epilepsy.

Epilepsy research
INTRODUCTION: To investigate the potential of using artificial intelligence (AI), specifically large language models (LLMs), for synthesizing information in a simulated randomized clinical trial (RCT) for an anti-seizure medication, cenobamate, demon...

Machine-learning random forest algorithms predict post-cycloplegic myopic corrections from noncycloplegic clinical data.

Optometry and vision science : official publication of the American Academy of Optometry
SIGNIFICANCE: Machine learning random forest algorithms were used to predict objective refractive outcomes after cycloplegic refraction using noncycloplegic clinical data. A classification model predicted post-cycloplegic myopia and could be useful i...