AIMC Topic: Reproducibility of Results

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Bioinspired, Shape-Morphing Scale Battery for Untethered Soft Robots.

Soft robotics
Geometrically multifunctional structures inspired by nature can address the challenges in the development of soft robotics. A bioinspired structure based on origami and kirigami can significantly enhance the stretchability and reliability of soft rob...

Convolutional neural network-based object detection model to identify gastrointestinal stromal tumors in endoscopic ultrasound images.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: We aimed to develop a convolutional neural network (CNN)-based object detection model for the discrimination of gastric subepithelial tumors, such as gastrointestinal stromal tumors (GISTs), and leiomyomas, in endoscopic ultrasoun...

A mechatronics data collection, image processing, and deep learning platform for clinical posture analysis: a technical note.

Physical and engineering sciences in medicine
Static and dynamic posture analysis was a critical clinical examination in physiotherapy and rehabilitation. It was a time-consuming task for clinicians, so a semi-automatic method can facilitate this process as well as provide well-documented medica...

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.

Scientific reports
Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantification of MFI requires time-consuming and rater-dependent manual segmentation techniques. A convolutional neural network (CNN) model was trained to se...

Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that inc...

Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods.

Nature communications
Efficient and precise base editors (BEs) for C-to-G transversion are highly desirable. However, the sequence context affecting editing outcome largely remains unclear. Here we report engineered C-to-G BEs of high efficiency and fidelity, with the seq...

Deep learning-based transformation of H&E stained tissues into special stains.

Nature communications
Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H&E) stain is most commonly used, special stains can provide additional contrast to different tissue components. Here, we demonstra...

Effect of alkaline treatment on the removal of contaminants of emerging concern from municipal biosolids: Modelling and optimization of process parameters using RSM and ANN coupled GA.

Chemosphere
The current study aimed in enhancing the efficiency of alkaline treatment for CECs remediation in biosolids through the application of RSM and ANN. Due to the seasonal variation of CECs in biosolids, a complete CECs profile over a period of three yea...