AIMC Topic: Humans

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A novel manipulator with needle insertion forces feedback for robot-assisted lumbar puncture.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The use of lumbar puncture for paediatric diagnosis and treatment, such as cerebrospinal fluid sampling and intracranial pressure measurements, is steadily increasing. However, the standard 'blind' technique makes it difficult to attain a...

Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation-Related Stroke.

Circulation
BACKGROUND: Atrial fibrillation (AF) is associated with substantial morbidity, especially when it goes undetected. If new-onset AF could be predicted, targeted screening could be used to find it early. We hypothesized that a deep neural network could...

A deep learning integrated radiomics model for identification of coronavirus disease 2019 using computed tomography.

Scientific reports
Since its first outbreak, Coronavirus Disease 2019 (COVID-19) has been rapidly spreading worldwide and caused a global pandemic. Rapid and early detection is essential to contain COVID-19. Here, we first developed a deep learning (DL) integrated radi...

Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.

Scientific reports
Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and i...

A scalable physician-level deep learning algorithm detects universal trauma on pelvic radiographs.

Nature communications
Pelvic radiograph (PXR) is essential for detecting proximal femur and pelvis injuries in trauma patients, which is also the key component for trauma survey. None of the currently available algorithms can accurately detect all kinds of trauma-related ...

Efficacy of Smart Speaker-Based Metamemory Training in Older Adults: Case-Control Cohort Study.

Journal of medical Internet research
BACKGROUND: Metamemory training (MMT) is a useful training strategy for improving cognitive functioning in the older adult population. Despite the advantages, there are limitations imposed by location and time constraints.

Thyroid gland delineation in noncontrast-enhanced CTs using deep convolutional neural networks.

Physics in medicine and biology
The purpose of this study is to develop a deep learning method for thyroid delineation with high accuracy, efficiency, and robustness in noncontrast-enhanced head and neck CTs. The cross-sectional analysis consisted of six tests, including randomized...

Patient journey through cases of depression from claims database using machine learning algorithms.

PloS one
Health insurance and acute hospital-based claims have recently become available as real-world data after marketing in Japan and, thus, classification and prediction using the machine learning approach can be applied to them. However, the methodology ...

Comparison of diagnostic performance between convolutional neural networks and human endoscopists for diagnosis of colorectal polyp: A systematic review and meta-analysis.

PloS one
Prospective randomized trials and observational studies have revealed that early detection, classification, and removal of neoplastic colorectal polyp (CP) significantly improve the prevention of colorectal cancer (CRC). The current effectiveness of ...