AIMC Topic: Humans

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Unifying invariant and variant features for graph out-of-distribution via probability of necessity and sufficiency.

Neural networks : the official journal of the International Neural Network Society
Graph Out-of-Distribution (OOD), requiring that models trained on biased data generalize to the unseen test data, has considerable real-world applications. One of the most mainstream methods is to extract the invariant subgraph by aligning the origin...

Combination of deep learning reconstruction and quantification for dynamic contrast-enhanced (DCE) MRI.

Magnetic resonance imaging
Dynamic contrast-enhanced (DCE) MRI is an important imaging tool for evaluating tumor vascularity that can lead to improved characterization of tumor extent and heterogeneity, and for early assessment of treatment response. However, clinical adoption...

Programmable ultrasound-mediated swarms manipulation of bacteria-red blood cell microrobots for tumor-specific thrombosis and robust photothermal therapy.

Trends in biotechnology
Despite the excellent advantages of biomicrorobots, such as autonomous navigation and targeting actuation, effective penetration and retention to deep lesion sites for effective therapy remains a longstanding challenge. Here, we present dual-engine c...

Neural networks for predicting etiological diagnosis of uveitis.

Eye (London, England)
BACKGROUND/OBJECTIVES: The large number and heterogeneity of causes of uveitis make the etiological diagnosis a complex task. The clinician must consider all the information concerning the ophthalmological and extra-ophthalmological features of the p...

Integrating Generative Artificial Intelligence Into Medical Education: Curriculum, Policy, and Governance Strategies.

Academic medicine : journal of the Association of American Medical Colleges
The rapid advancement of generative artificial intelligence (GAI) is poised to revolutionize medical education, clinical decision-making, and health care workflow. Despite considerable interest and a surfeit of newly available tools, medical educator...

Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.

Journal of applied clinical medical physics
PURPOSE: Cardiotoxicity is one of the major concerns in breast cancer treatment, significantly affecting patient outcomes. To improve the likelihood of favorable outcomes for breast cancer survivors, it is essential to carefully balance the potential...

Improved deep learning-based IVIM parameter estimation via the use of more "realistic" simulated brain data.

Medical physics
BACKGROUND: Due to the low signal-to-noise ratio (SNR) and the limited number of b-values, precise parameter estimation of intravoxel incoherent motion (IVIM) imaging remains an open issue to date, especially for brain imaging where the relatively sm...

Classifying Alzheimer's Disease Using a Finite Basis Physics Neural Network.

Microscopy research and technique
The disease amyloid plaques, neurofibrillary tangles, synaptic dysfunction, and neuronal death gradually accumulate throughout Alzheimer's disease (AD), resulting in cognitive decline and functional disability. The challenges of dataset quality, inte...

Interactively Fusing Global and Local Features for Benign and Malignant Classification of Breast Ultrasound Images.

Ultrasound in medicine & biology
OBJECTIVE: Breast ultrasound (BUS) is used to classify benign and malignant breast tumors, and its automatic classification can reduce subjectivity. However, current convolutional neural networks (CNNs) face challenges in capturing global features, w...

Assessing the prognostic impact of body composition phenotypes on surgical outcomes and survival in patients with spinal metastasis: a deep learning approach to preoperative CT analysis.

Journal of neurosurgery. Spine
OBJECTIVE: The prognostic significance of body composition phenotypes for survival in patients undergoing surgical intervention for spinal metastases has not yet been elucidated. This study aimed to elucidate the impact of body composition phenotypes...