AI Medical Compendium Topic

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Disease Models, Animal

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Robotic assistance for percutaneous needle insertion in the kidney: preclinical proof on a swine animal model.

European radiology experimental
BACKGROUND: We evaluated the accuracy, safety, and feasibility of a computed tomography (CT)-guided robotic assistance system for percutaneous needle placement in the kidney.

A deep learning-based toolbox for Automated Limb Motion Analysis (ALMA) in murine models of neurological disorders.

Communications biology
In neuroscience research, the refined analysis of rodent locomotion is complex and cumbersome, and access to the technique is limited because of the necessity for expensive equipment. In this study, we implemented a new deep learning-based open-sourc...

Structural, functional and molecular pathogenesis of pelvic organ prolapse in patient and deficient mice.

Aging
Pelvic organ prolapse is a worldwide health problem to elderly women. Understanding its pathogenesis and an ideal animal model are crucial to developing promising treatments. The present study aimed to investigate new clinical significance and detail...

Deep learning is widely applicable to phenotyping embryonic development and disease.

Development (Cambridge, England)
Genome editing simplifies the generation of new animal models for congenital disorders. However, the detailed and unbiased phenotypic assessment of altered embryonic development remains a challenge. Here, we explore how deep learning (U-Net) can auto...

Applying deep learning to quantify empty lacunae in histologic sections of osteonecrosis of the femoral head.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Osteonecrosis of the femoral head (ONFH) is a disease in which inadequate blood supply to the subchondral bone causes the death of cells in the bone marrow. Decalcified histology and assessment of the percentage of empty lacunae are used to quantify ...

Deep Learning to Decipher the Progression and Morphology of Axonal Degeneration.

Cells
Axonal degeneration (AxD) is a pathological hallmark of many neurodegenerative diseases. Deciphering the morphological patterns of AxD will help to understand the underlying mechanisms and develop effective therapies. Here, we evaluated the progressi...

Peak learning of mass spectrometry imaging data using artificial neural networks.

Nature communications
Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size ...

Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that inc...

Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.

Behavioural brain research
Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI). Unfortunately, these gains are primarily task specific; where reach training only improves reaching, step training only improves stepping and stand t...

Artificial intelligence-driven phenotyping of zebrafish psychoactive drug responses.

Progress in neuro-psychopharmacology & biological psychiatry
Zebrafish (Danio rerio) are rapidly emerging in biomedicine as promising tools for disease modelling and drug discovery. The use of zebrafish for neuroscience research is also growing rapidly, necessitating novel reliable and unbiased methods of neur...