AIMC Topic: Humans

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Intra-class progressive and adaptive self-distillation.

Neural networks : the official journal of the International Neural Network Society
In recent years, knowledge distillation (KD) has become widely used in compressing models, training compact and efficient students to reduce computational load and training time due to the increasing parameters in deep neural networks. To minimize tr...

AAPMatcher: Adaptive attention pruning matcher for accurate local feature matching.

Neural networks : the official journal of the International Neural Network Society
Local feature matching, which seeks to establish correspondences between two images, serves as a fundamental component in numerous computer vision applications, such as camera tracking and 3D mapping. Recently, Transformer has demonstrated remarkable...

Population Health in Neurology and the Transformative Promise of Artificial Intelligence and Large Language Models.

Seminars in neurology
This manuscript examines the expanding role of population health strategies in neurology, emphasizing systemic approaches that address neurological health at a community-wide level. Key themes include interdisciplinary training in public health, poli...

Risk prediction models for frailty in older adults: A systematic review and critical appraisal.

International journal of nursing studies
BACKGROUND: Frailty can lead to increased adverse health outcomes in older adults. Risk prediction models for frailty have benefits in guiding the prevention. Studies have increasingly focused on the development of risk prediction models for frailty ...

Informational embodiment: Computational role of information structure in codes and robots.

Physics of life reviews
The body morphology plays an important role in the way information is perceived and processed by an agent. We address an information theory (IT) account on how the precision of sensors, the accuracy of motors, their placement, the body geometry, shap...

Deep Guess acceleration for explainable image reconstruction in sparse-view CT.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sparse-view Computed Tomography (CT) is an emerging protocol designed to reduce X-ray dose radiation in medical imaging. Reconstructions based on the traditional Filtered Back Projection algorithm suffer from severe artifacts due to sparse data. In c...

External Validation of a Machine Learning Model to Diagnose Kawasaki Disease.

The Journal of pediatrics
We investigated the generalizability of a machine learning model trained to predict Kawasaki disease using laboratory and clinical data. The algorithm performed with >89% accuracy at 3 children's hospitals across the United States, demonstrating its ...

Day-to-day dynamics of facial emotion expressions in posttraumatic stress disorder.

Journal of affective disorders
Facial expressions are an essential component of emotions that may reveal mechanisms maintaining posttraumatic stress disorder (PTSD). However, most research on emotions in PTSD has relied on self-reports, which only capture subjective affect. The fe...

Deformable image registration with strategic integration pyramid framework for brain MRI.

Magnetic resonance imaging
Medical image registration plays a crucial role in medical imaging, with a wide range of clinical applications. In this context, brain MRI registration is commonly used in clinical practice for accurate diagnosis and treatment planning. In recent yea...

Radiomics-based MRI model to predict hypoperfusion in lacunar infarction.

Magnetic resonance imaging
BACKGROUND: Approximately 20-30 % of patients with acute ischemic stroke due to lacunar infarction experience early neurological deterioration (END) within the first three days after onset, leading to disability or more severe sequelae. Hemodynamic p...