AIMC Topic: Neural Networks, Computer

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Artificial Intelligent and Internet of Things framework for sustainable hazardous waste management in hospitals.

Waste management (New York, N.Y.)
Healthcare activities in hospitals generate numerous types of post-use waste materials that can be classified as hazardous. This study proposes an Artificial Intelligence (AI) and Internet of Things (IoT) integrated framework for secure and efficient...

RNN-Based Full Waveform Inversion for Robust Multi-Parameter Bone Quantitative Imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The full waveform inversion (FWI) method plays a significant role in bone quantitative imaging. It is shown that even a small deviation in transducer positions can lead to a considerable variation in frequency-domain signals...

TasteNet: A novel deep learning approach for EEG-based basic taste perception recognition using CEEMDAN domain entropy features.

Journal of neuroscience methods
BACKGROUND: Taste perception is the process by which the gustatory system detects and interprets chemical stimuli from food and beverages, involving activation of taste receptors on the tongue. Analyzing taste perception is essential for understandin...

Ovarian Cancer Detection in Ascites Cytology with Weakly Supervised Model on Nationwide Data Set.

The American journal of pathology
Conventional ascitic fluid cytology for detecting ovarian cancer is limited by its low sensitivity. To address this issue, this multicenter study developed patch image (PI)-based fully supervised convolutional neural network (CNN) models and clusteri...

Massive experimental quantification allows interpretable deep learning of protein aggregation.

Science advances
Protein aggregation is a pathological hallmark of more than 50 human diseases and a major problem for biotechnology. Methods have been proposed to predict aggregation from sequence, but these have been trained and evaluated on small and biased experi...

A new strategy for Cas protein recognition based on graph neural networks and SMILES encoding.

Scientific reports
The CRISPR-Cas system, an adaptive immune mechanism found in bacteria and archaea, has evolved into a promising genomic editing tool, with various types of Cas proteins playing a crucial role. In this study, we developed a set of strategies for minin...

A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images.

Scientific reports
Recent advancements in deep learning have significantly impacted medical image processing domain, enabling sophisticated and accurate diagnostic tools. This paper presents a novel hybrid deep learning framework that combines convolutional neural netw...

Self-supervised learning for label-free segmentation in cardiac ultrasound.

Nature communications
Segmentation and measurement of cardiac chambers from ultrasound is critical, but laborious and poorly reproducible. Neural networks can assist, but supervised approaches require the same problematic manual annotations. We build a pipeline for self-s...

Pioneering AI-guided fluorescence-like navigation in urological surgery: real-time ureter segmentation during robot-assisted radical cystectomy using convolutional neural network.

Journal of robotic surgery
Artificial intelligence (AI)-driven intraoperative navigation in urological surgery can enhance surgical precision through real-time structure identification and tracking. This study describes a novel AI solution that enables real-time fluorescence-l...

3D tooth identification for forensic dentistry using deep learning.

BMC oral health
The classification of intraoral teeth structures is a critical component in modern dental analysis and forensic dentistry. Traditional methods, relying on 2D imaging, often suffer from limitations in accuracy and comprehensiveness due to the complex ...