AIMC Topic: Reproducibility of Results

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Semi-Supervised Anomaly Detection in Video-Surveillance Scenes in the Wild.

Sensors (Basel, Switzerland)
Surveillance cameras are being installed in many primary daily living places to maintain public safety. In this video-surveillance context, anomalies occur only for a very short time, and very occasionally. Hence, manual monitoring of such anomalies ...

Robot-assisted donor hysterectomy in uterus transplantation - a modality to increase reproducibility.

Ginekologia polska
Uterus transplantation is a non-lifesaving vascularized composite allotransplantation procedure requiring immunosuppression until removal of the graft. The focus of uterus transplantation is changing regarding refining individual treatment procedures...

Deep probabilistic tracking of particles in fluorescence microscopy images.

Medical image analysis
Tracking of particles in temporal fluorescence microscopy image sequences is of fundamental importance to quantify dynamic processes of intracellular structures as well as virus structures. We introduce a probabilistic deep learning approach for fluo...

Automatic cortical target point localisation in MRI for transcranial magnetic stimulation via a multi-resolution convolutional neural network.

International journal of computer assisted radiology and surgery
PURPOSE: Transcranial magnetic stimulation (TMS) is a growing therapy for a variety of psychiatric and neurological disorders that arise from or are modulated by cortical regions of the brain represented by singular 3D target points. These target poi...

Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm.

Applied microbiology and biotechnology
Plant callus is generally considered to be a mass of undifferentiated cells and can be used for secondary metabolite production, physiological studies, and plant transformation/regeneration. However, there are several types of callus with different m...

Alignment-Free Antimicrobial Peptide Predictors: Improving Performance by a Thorough Analysis of the Largest Available Data Set.

Journal of chemical information and modeling
In the last two decades, a large number of machine-learning-based predictors for the activities of antimicrobial peptides (AMPs) have been proposed. These predictors differ from one another in the learning method and in the training and testing data ...

Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images.

Scientific reports
Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death within 1 year of fracture. This study proposes an automated method to detect pelvic fractures on 3-dimensional computed tomography (3D-CT). Deep convo...

Lung Lesion Localization of COVID-19 From Chest CT Image: A Novel Weakly Supervised Learning Method.

IEEE journal of biomedical and health informatics
Chest computed tomography (CT) image data is necessary for early diagnosis, treatment, and prognosis of Coronavirus Disease 2019 (COVID-19). Artificial intelligence has been tried to help clinicians in improving the diagnostic accuracy and working ef...

Multi-Parametric Fusion of 3D Power Doppler Ultrasound for Fetal Kidney Segmentation Using Fully Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Kidney development is key to the long-term health of the fetus. Renal volume and vascularity assessed by 3D ultrasound (3D-US) are known markers of wellbeing, however, a lack of real-time image segmentation solutions preclude these measures being use...