AIMC Topic: Humans

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Deep learning for brain metastasis detection and segmentation in longitudinal MRI data.

Medical physics
PURPOSE: Brain metastases (BM) occur frequently in patients with metastatic cancer. Early and accurate detection of BM is essential for treatment planning and prognosis in radiation therapy. Due to their tiny sizes and relatively low contrast, small ...

Machine Learning to Delineate Surgeon and Clinical Factors That Anticipate Positive Surgical Margins After Robot-Assisted Radical Prostatectomy.

Journal of endourology
Automated performance metrics (APMs), derived from instrument kinematic and systems events data during robotic surgery, are validated objective measures of surgeon performance. Our previous studies showed that APMs are strong outcome predictors of u...

Nucleoside Triphosphate Hydrolases Assay in Toxoplasm gondii and Neospora caninum for High-Throughput Screening using a Robot Arm.

Journal of visualized experiments : JoVE
Protozoan parasites infect humans and many warm-blooded animals. Toxoplasma gondii, a major protozoan parasite, is commonly found in HIV-positive patients, organ transplant recipients and pregnant women, resulting in the severe health condition, Toxo...

A Lightweight Subgraph-Based Deep Learning Approach for Fall Recognition.

Sensors (Basel, Switzerland)
Falls pose a great danger to social development, especially to the elderly population. When a fall occurs, the body's center of gravity moves from a high position to a low position, and the magnitude of change varies among body parts. Most existing f...

Deep Learning-Based Segmentation of Post-Mortem Human's Olfactory Bulb Structures in X-ray Phase-Contrast Tomography.

Tomography (Ann Arbor, Mich.)
The human olfactory bulb (OB) has a laminar structure. The segregation of cell populations in the OB image poses a significant challenge because of indistinct boundaries of the layers. Standard 3D visualization tools usually have a low resolution and...

A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation.

Radiation oncology (London, England)
BACKGROUND: We describe and evaluate a deep network algorithm which automatically contours organs at risk in the thorax and pelvis on computed tomography (CT) images for radiation treatment planning.

SAFARI: shape analysis for AI-segmented images.

BMC medical imaging
BACKGROUND: Recent developments to segment and characterize the regions of interest (ROI) within medical images have led to promising shape analysis studies. However, the procedures to analyze the ROI are arbitrary and vary by study. A tool to transl...

Face mediated human-robot interaction for remote medical examination.

Scientific reports
Realtime visual feedback from consequences of actions is useful for future safety-critical human-robot interaction applications such as remote physical examination of patients. Given multiple formats to present visual feedback, using face as feedback...

Accurate somatic variant detection using weakly supervised deep learning.

Nature communications
Identification of somatic mutations in tumor samples is commonly based on statistical methods in combination with heuristic filters. Here we develop VarNet, an end-to-end deep learning approach for identification of somatic variants from aligned tumo...

Multiplexed high-throughput localized electroporation workflow with deep learning-based analysis for cell engineering.

Science advances
Manipulation of cells for applications such as biomanufacturing and cell-based therapeutics involves introducing biomolecular cargoes into cells. However, successful delivery is a function of multiple experimental factors requiring several rounds of ...