AIMC Topic: Humans

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Object and anatomical feature recognition in surgical video images based on a convolutional neural network.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence-enabled techniques can process large amounts of surgical data and may be utilized for clinical decision support to recognize or forecast adverse events in an actual intraoperative scenario. To develop an image-guided ...

Classification of impedance cardiography dZ/dt complex subtypes using pattern recognition artificial neural networks.

Biomedizinische Technik. Biomedical engineering
In impedance cardiography (ICG), the detection of dZ/dt signal (ICG) characteristic points, especially the X point, is a crucial step for the calculation of hemodynamic parameters such as stroke volume (SV) and cardiac output (CO). Unfortunately, for...

Artificial intelligence for quality assurance in radiotherapy.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
In radiotherapy, patient-specific quality assurance is very time-consuming and causes machine downtime. It consists of testing (using measurement with a phantom and detector) if a modulated plan is correctly delivered by a treatment unit. Artificial ...

Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topi...

Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

Histopathology
AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article w...

Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms.

Gait & posture
PURPOSE: Machine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropr...

Universum based Lagrangian twin bounded support vector machine to classify EEG signals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The detection of brain-related problems and neurological disorders like epilepsy, sleep disorder, and so on is done by using electroencephalogram (EEG) signals which contain noisy signals and outliers. Universum data contain...

Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance.

International journal of computer assisted radiology and surgery
PURPOSE: The current study aimed to propose a Deep Learning (DL) and Augmented Reality (AR) based solution for a in-vivo robot-assisted radical prostatectomy (RARP), to improve the precision of a published work from our group. We implemented a two-st...

Analysis of cognitive impairment in schizophrenia based on machine learning: Interaction between psychological stress and immune system.

Neuroscience letters
The interaction between psychological stress and immune system may be associated with the cognitive impairment of schizophrenia. To employ machine learning algorithms to examine patterns of stress-immune networks with cognitive impairment in chronic ...