AIMC Topic: Humans

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Machine learning for the prediction of pathologic pneumatosis intestinalis.

Surgery
BACKGROUND: The radiographic finding of pneumatosis intestinalis can indicate a spectrum of underlying processes ranging from a benign finding to a life-threatening condition. Although radiographic pneumatosis intestinalis is relatively common, there...

Internet of medical things embedding deep learning with data augmentation for mammogram density classification.

Microscopy research and technique
Females are approximately half of the total population worldwide, and most of them are victims of breast cancer (BC). Computer-aided diagnosis (CAD) frameworks can help radiologists to find breast density (BD), which further helps in BC detection pre...

A learning robot for cognitive camera control in minimally invasive surgery.

Surgical endoscopy
BACKGROUND: We demonstrate the first self-learning, context-sensitive, autonomous camera-guiding robot applicable to minimally invasive surgery. The majority of surgical robots nowadays are telemanipulators without autonomous capabilities. Autonomous...

Diagnosing Atrial Septal Defect from Electrocardiogram with Deep Learning.

Pediatric cardiology
The heart murmur associated with atrial septal defects is often faint and can thus only be detected by chance. Although electrocardiogram examination can prompt diagnoses, identification of specific findings remains a major challenge. We demonstrate ...

A novel master-slave intraocular surgical robot with force feedback.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Intraocular surgery is one of the most challenging microsurgeries. Unintended movements of human hand and lack of force feedback can seriously affect surgical safety.

Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer.

International journal of cancer
High levels of microsatellite instability (MSI-H) occurs in about 15% of sporadic colorectal cancer (CRC) and is an important predictive marker for response to immune checkpoint inhibitors. To test the feasibility of a deep learning (DL)-based classi...

A through-focus scanning optical microscopy dimensional measurement method based on deep-learning classification model.

Journal of microscopy
Through-focus scanning optical microscopy (TSOM) is an economical, non-contact and nondestructive method for rapid measurement of three-dimensional nanostructures. There are two methods using TSOM image to measure the dimensions of one sample, includ...

Automated Segmentation of the Median Nerve in the Carpal Tunnel using U-Net.

Ultrasound in medicine & biology
Nerve area and motion in carpal tunnel syndrome (CTS) are currently under investigation in terms of prognostic potential. Therefore, there is increasing interest in non-invasive measurement of the nerve using ultrasound. Manual segmentation is time c...

Deep learning early warning system for embryo culture conditions and embryologist performance in the ART laboratory.

Journal of assisted reproduction and genetics
Staff competency is a crucial component of the in vitro fertilization (IVF) laboratory quality management system because it impacts clinical outcomes and informs the key performance indicators (KPIs) used to continuously monitor and assess culture co...

Unwrapping the phase portrait features of adventitious crackle for auscultation and classification: a machine learning approach.

Journal of biological physics
The paper delves into the plausibility of applying fractal, spectral, and nonlinear time series analyses for lung auscultation. The thirty-five sound signals of bronchial (BB) and pulmonary crackle (PC) analysed by fast Fourier transform and wavelet ...