AIMC Topic: Neural Networks, Computer

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Cell morphology-based machine learning models for human cell state classification.

NPJ systems biology and applications
Herein, we implement and access machine learning architectures to ascertain models that differentiate healthy from apoptotic cells using exclusively forward (FSC) and side (SSC) scatter flow cytometry information. To generate training data, colorecta...

Prediction model for the risk of osteoporosis incorporating factors of disease history and living habits in physical examination of population in Chongqing, Southwest China: based on artificial neural network.

BMC public health
BACKGROUND: Osteoporosis is a gradually recognized health problem with risks related to disease history and living habits. This study aims to establish the optimal prediction model by comparing the performance of four prediction models that incorpora...

External features enriched model for biomedical question answering.

BMC bioinformatics
BACKGROUND: Biomedical question answering (QA) is a sub-task of natural language processing in a specific domain, which aims to answer a question in the biomedical field based on one or more related passages and can provide people with accurate healt...

Convolutional fusion network for monaural speech enhancement.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural network (CNN) based methods, such as the convolutional encoder-decoder network, offer state-of-the-art results in monaural speech enhancement. In the conventional encoder-decoder network, large kernel size is often used to enhanc...

Co-occurrence balanced time series classification for the semi-supervised recognition of surgical smoke.

International journal of computer assisted radiology and surgery
PURPOSE: Automatic recognition and removal of smoke in surgical procedures can reduce risks to the patient by supporting the surgeon. Surgical smoke changes its visibility over time, impacting the vision depending on its amount and the volume of the ...

Identify dominant dimensions of 3D hand shapes using statistical shape model and deep neural network.

Applied ergonomics
Hand anthropometry is one of the fundamentals of ergonomic research and product design. Many studies have been conducted to analyze the hand dimensions among different populations, however, the definitions and the numbers of those dimensions were usu...

A deep learning model for detection and tracking in high-throughput images of organoid.

Computers in biology and medicine
Organoid, an in vitro 3D culture, has extremely high similarity with its source organ or tissue, which creates a model in vitro that simulates the in vivo environment. Organoids have been extensively studied in cell biology, precision medicine, drug ...

Prediction of Head Movement in 360-Degree Videos Using Attention Model.

Sensors (Basel, Switzerland)
In this paper, we propose a prediction algorithm, the combination of Long Short-Term Memory (LSTM) and attention model, based on machine learning models to predict the vision coordinates when watching 360-degree videos in a Virtual Reality (VR) or Au...

Machine learning prediction of sleep stages in dairy cows from heart rate and muscle activity measures.

Scientific reports
Sleep is important for cow health and shows promise as a tool for assessing welfare, but methods to accurately distinguish between important sleep stages are difficult and impractical to use with cattle in typical farm environments. The objective of ...

Finding gene network topologies for given biological function with recurrent neural network.

Nature communications
Searching for possible biochemical networks that perform a certain function is a challenge in systems biology. For simple functions and small networks, this can be achieved through an exhaustive search of the network topology space. However, it is di...