AIMC Topic: Humans

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SE-ATT-YOLO- A deep learning driven ultrasound based respiratory motion compensation system for precision radiotherapy.

Computers in biology and medicine
OBJECTIVE: The therapeutic management of neoplasm employs high level energy beam to ablate malignant cells, which can cause collateral damage to adjacent normal tissue. Furthermore, respiration-induced organ motion, during radiotherapy can lead to si...

CNN-extracted features generate synthetic fMRI responses to unseen images.

Vision research
Inspired by biological vision, convolutional neural networks (CNNs) have tackled challenging image recognition problems once considered the sole purview of human expertise. In turn, CNNs are now widely used as a framework for studying human vision. T...

Triclosan exposure potentiates ischemic stroke risk: Multi-omics integration and molecular docking unveil neurotoxic mechanisms.

Ecotoxicology and environmental safety
This study applied network toxicology and multimodal biological approaches integrated with machine learning to systematically identify four TCS-IS-related genes, providing a comprehensive understanding of the pathophysiological relationship between t...

Large language models and women's health: a digital companion for informed decision-making.

Archives of gynecology and obstetrics
The integration of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT, in gynecology and obstetrics has the potential to significantly transform patient care. These AI-driven tools provide continuous access to inform...

Transcriptomic analysis reveals novel targets in benign schwannoma using machine learning.

Neuroscience
BACKGROUND & OBJECTIVE: This study aimed to identify key immune-related biomarkers of benign schwannoma through machine learning-assisted transcriptomic and single-cell analyses, and to construct a predictive model for disease evaluation.

Unsupervised single-image super-resolution for infant brain MRI.

NeuroImage
Acquiring high-resolution (HR) MR images of infant brains is challenging due to lengthy scan times and limited subject compliance. Image super-resolution (SR) techniques can generate HR images from low-resolution (LR) inputs, reducing the need for ex...

Deep learning dosiomics in grade 4 radiation-induced lymphopenia prediction in radiotherapy for esophageal cancer: a multi-center study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To investigate the feasibility and accuracy of using deep learning and dosiomics features, as well as their combination with dose-volume histogram (DVH) parameters and clinical factors to predict grade 4 radiation-induced lymphopenia (G4RIL)...

Accelerating vaccine development: Plug-and-play platforms for emerging infectious diseases.

Virus research
Emerging pathogens underscore an urgent need for rapidly developed vaccines to minimize mortality and societal disruption. Traditional vaccine development requires time spans of years, making it ill-suited to fast evolving viruses that can overwhelm ...

Chinese EFL students' perceptions about the role of artificial intelligence (AI) technologies in their second language (L2) self-concept.

Acta psychologica
The applications of Artificial Intelligence (AI) technologies to second or foreign language (L2) education have recently been the focus of several studies in the literature. However, the impact of AI tools on students' psychological-affective states ...

Significance of Papillary and Trabecular Muscular Volume in Right Ventricular Volumetry with Cardiac MR Imaging.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: Pulmonary valve regurgitation after repaired Tetralogy of Fallot (TOF) or double-outlet right ventricle (DORV) causes hypertrophy and papillary muscle enlargement. Cardiac magnetic resonance imaging (CMR) can evaluate the right ventricular (...