AIMC Topic: Humans

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Predicting Recurrence After Surgical Resection for High-Risk Localized Renal Cell Carcinoma: A Radiomics Clinical Integration Approach.

The Journal of urology
PURPOSE: Adjuvant immunotherapy for clear cell renal cell carcinoma (ccRCC) is controversial because of the absence of reliable biomarkers for identifying patients most likely to benefit. The aim of this study was to develop and validate a quantitati...

Evaluating Large Language Models on Aerospace Medicine Principles.

Wilderness & environmental medicine
IntroductionLarge language models (LLMs) hold immense potential to serve as clinical decision-support tools for Earth-independent medical operations. However, the generation of incorrect information may be misleading or even harmful when applied to c...

S-Net: Learning spectral-spatio self-similarity for hyperspectral image super-resolution.

Neural networks : the official journal of the International Neural Network Society
As an economically feasible approach for hyperspectral image (HSI) super-resolution, fusing HSI with multispectral image (MSI) utilizes the complementary nature of cross-modality information. Given the common presence of repetitive textures and struc...

Self-supervised spatial-temporal contrastive network for EEG-based brain network classification.

Neural networks : the official journal of the International Neural Network Society
Electroencephalogram (EEG)-based brain network analysis has shown promise in brain disease research by revealing the complex connectivity among brain regions. However, existing methods struggle to fully utilize the large amounts of unlabeled data to ...

MSCViT: A small-size ViT architecture with multi-scale self-attention mechanism for tiny datasets.

Neural networks : the official journal of the International Neural Network Society
Vision Transformer (ViT) has demonstrated significant potential in various vision tasks due to its strong ability in modeling long-range dependencies. However, such success is largely fueled by training on massive samples. In real applications, the l...

A Comparative Bicentric Study on Ultrasound Education for Students: App- and AI-Supported Learning Versus Traditional Hands-on Instruction (AI-Teach Study).

Academic radiology
BACKGROUND: The integration of artificial intelligence (AI) into medical education presents significant opportunities for enhancing teaching methods and student learning outcomes. Despite its potential benefits, the implementation of AI in curricula ...

Documentation, Coding, and Billing for Neurologic Services and Procedures.

Seminars in neurology
Documentation, coding, and billing (claims submission) are foundational to neurologic practice in the United States, enabling accurate reimbursement, effective communication, and data-driven advancements in patient care, research, and education. Neur...

Global-Local Feature Fusion Network Based on Nonlinear Spiking Neural Convolutional Model for MRI Brain Tumor Segmentation.

International journal of neural systems
Due to the differences in size, shape, and location of brain tumors, brain tumor segmentation differs greatly from that of other organs. The purpose of brain tumor segmentation is to accurately locate and segment tumors from MRI images to assist doct...

Machine learning models for minimizing aggravation in work-related musculoskeletal disorders among slaughterhouse workers.

Work (Reading, Mass.)
BackgroundWork-related musculoskeletal disorders (WMSDs) are common in Brazilian slaughterhouses. The repetitive and strenuous nature of meat processing, especially in slaughterhouses, makes employees highly susceptible to developing WMSDs. Prolonged...

MED-NCA: Bio-inspired medical image segmentation.

Medical image analysis
The reliance on computationally intensive U-Net and Transformer architectures significantly limits their accessibility in low-resource environments, creating a technological divide that hinders global healthcare equity, especially in medical diagnost...