AIMC Topic: Neural Networks, Computer

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Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning.

Nature communications
The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of pathologists offers a unique opportunity for the use of artificial intelligence assistance systems ...

Improving depth-of-interaction resolution in pixellated PET detectors using neural networks.

Physics in medicine and biology
Parallax error is a common issue in high-resolution preclinical positron emission tomography (PET) scanners as well as in clinical scanners that have a long axial field of view (FOV), which increases estimation uncertainty of the annihilation positio...

Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographs.

Clinical oral investigations
OBJECTIVE: To evaluate the performance of a new artificial intelligence (AI)-driven tool for tooth detection and segmentation on panoramic radiographs.

Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction.

Environmental science and pollution research international
There is a need to develop an accurate and reliable model for predicting suspended sediment load (SSL) because of its complexity and difficulty in practice. This is due to the fact that sediment transportation is extremely nonlinear and is directed b...

An Acoustic Sensing Gesture Recognition System Design Based on a Hidden Markov Model.

Sensors (Basel, Switzerland)
Many human activities are tactile. Recognizing how a person touches an object or a surface surrounding them is an active area of research and it has generated keen interest within the interactive surface community. In this paper, we compare two machi...

Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia.

PloS one
Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signal...

Neural networks differentiate between Middle and Later Stone Age lithic assemblages in eastern Africa.

PloS one
The Middle to Later Stone Age transition marks a major change in how Late Pleistocene African populations produced and used stone tool kits, but is manifest in various ways, places and times across the continent. Alongside changing patterns of raw ma...

Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.

PloS one
A new computer-aided detection scheme is proposed, the 3D U-Net convolutional neural network, based on multiscale features of transfer learning to automatically detect pulmonary nodules from the thoracic region containing background and noise. The te...

Multispectral Imaging for Automated Tissue Identification of Normal Human Surgical Specimens.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Safe surgery requires the accurate discrimination of tissue intraoperatively. We assess the feasibility of using multispectral imaging and deep learning to enhance surgical vision by automated identification of normal human head and neck t...

A direct approach for function approximation on data defined manifolds.

Neural networks : the official journal of the International Neural Network Society
In much of the literature on function approximation by deep networks, the function is assumed to be defined on some known domain, such as a cube or a sphere. In practice, the data might not be dense on these domains, and therefore, the approximation ...