AIMC Topic: Humans

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Radiomics and artificial intelligence for predicting pituitary neuroendocrine tumor consistency: a systematic review and meta-analysis.

Neurosurgical review
Pituitary neuroendocrine tumors (PitNETs) represent approximately 16% of primary brain tumors. Tumor consistency, whether soft or hard, directly affects surgical strategy, extent of resection, and risk of complications. This study aimed to perform a ...

Proteomics-Driven Cancer Biomarkers for Early Detection and Targeted Therapy: Insights from the Middle East.

Journal of proteome research
Proteomics has become a transformative tool in oncology, offering unique opportunities for early detection, diagnosis, and cancer stratification. By enabling large-scale analysis of protein expression, interactions, and post-translational modificatio...

The alternative splicing landscape of hepatocellular carcinoma and its potential for HCC detection.

Hepatology communications
BACKGROUND: Pre-mRNA alternative splicing contributes to oncogenic gene expression in hepatocellular carcinoma (HCC), and some oncogenic isoforms escape the tumor into circulation. This study aimed to characterize the alternative splicing landscape o...

Token-splitting improves GPT-4.1 performance on plastic surgery exams: implications for AI-Assisted medical education.

Medical education online
Large language models (LLMs), such as ChatGPT, have demonstrated impressive performance on general medical examinations; however, their effectiveness significantly declines in specialized board examinations due to limited domain-specific training dat...

Orthogonal Biochemical Sensing for Concentration-Independent Bacterial Fingerprinting.

Analytical chemistry
Array-based biosensors hold substantial promise for rapid bacterial identification. However, conventional approaches face two key limitations: their reliance on nonspecific interactions with bacterial surfaces hinders biochemical interpretation, and ...

Spiking world model with multicompartment neurons for model-based reinforcement learning.

Proceedings of the National Academy of Sciences of the United States of America
Brain-inspired spiking neural networks (SNNs) have garnered significant research attention in algorithm design and perception applications. However, their potential in the decision-making domain, particularly in model-based reinforcement learning, re...

Development and validation of a predictive model for postoperative acute respiratory distress syndrome in patients with type A aortic dissection based on the 2023 updated definition.

Respiratory research
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common complication after type A aortic dissection surgery and often leads to worsened clinical outcomes for patients. The early prediction of postoperative ARDS is a crucial challenge in cl...

Artificial Intelligence in Ocular Drug Delivery: Precision Drug Delivery's New Horizon.

AAPS PharmSciTech
BACKGROUND: Artificial intelligence is emerging as a transformative force in pharmaceutical sciences by enabling data-driven decision-making, automation, and predictive modeling. In ocular drug delivery, where therapeutic efficacy is hindered by comp...

Noninvasive CT radiomics-clinical model accurately classifies anhydrous uric acid stones: a multicenter study.

World journal of urology
BACKGROUND: Urolithiasis, particularly anhydrous uric acid stones (AUAs), imposes significant clinical and economic burdens. Accurate preoperative differentiation of AUAs from other stone types remains challenging, yet essential for personalized pati...

Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients.

BMC musculoskeletal disorders
BACKGROUND: Opioid overuse is a costly and significant problem in the United States. Medical specialties including surgery are a contributor to opioid prescriptions while having few clear prescribing guidelines. Machine learning predictive tools can ...