AIMC Topic: Neural Networks, Computer

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Deception detection with machine learning: A systematic review and statistical analysis.

PloS one
Several studies applying Machine Learning to deception detection have been published in the last decade. A rich and complex set of settings, approaches, theories, and results is now available. Therefore, one may find it difficult to identify trends, ...

Visual classification of pressure injury stages for nurses: A deep learning model applying modern convolutional neural networks.

Journal of advanced nursing
AIMS: To develop a deep learning model for pressure injury stages classification based on real-world photographs and compare its performance with that of clinical nurses to seek the opportunity of its application in clinical settings.

Detection of aspiration from images of a videofluoroscopic swallowing study adopting deep learning.

Oral radiology
OBJECTIVES: A videofluoroscopic swallowing study (VFSS) is conducted to detect aspiration. However, aspiration occurs within a short time and is difficult to detect. If deep learning can detect aspirations with high accuracy, clinicians can focus on ...

Development of a deep learning-based tool to assist wound classification.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
This paper presents a deep learning-based wound classification tool that can assist medical personnel in non-wound care specialization to classify five key wound conditions, namely deep wound, infected wound, arterial wound, venous wound, and pressur...

Hierarchical deep learning with Generative Adversarial Network for automatic cardiac diagnosis from ECG signals.

Computers in biology and medicine
Cardiac disease is the leading cause of death in the US. Accurate heart disease detection is critical to timely medical treatment to save patients' lives. Routine use of the electrocardiogram (ECG) is the most common method for physicians to assess t...

Pediatric age estimation from thoracic and abdominal CT scout views using deep learning.

Scientific reports
Age assessment is regularly used in clinical routine by pediatric endocrinologists to determine the physical development or maturity of children and adolescents. Our study investigates whether age assessment can be performed using CT scout views from...

Multimodal convolutional neural networks based on the Raman spectra of serum and clinical features for the early diagnosis of prostate cancer.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
We collected surface-enhanced Raman spectroscopy (SERS) data from the serum of 729 patients with prostate cancer or benign prostatic hyperplasia (BPH), corresponding to their pathological results, and built an artificial intelligence-assisted diagnos...

Operational parameter prediction of electrocoagulation system in a rural decentralized water treatment plant by interpretable machine learning model.

Journal of environmental management
Electrocoagulation (EC) is a promising alternative for decentralized drinking water treatment in rural areas as a chemical-free technology. However, seasonal fluctuations of water quality in influent remain a significant challenge for rural decentral...

Prediction of cooling effect of constant temperature community bin based on BP neural network.

International journal of biometeorology
In order to explore the influence of outdoor microclimate on the cooling effect of constant temperature community bin, the temperature prediction model was predicted. The temperature and microclimate data sets of the community bin were collected in s...

A Lightweight Deep Learning Based Microwave Brain Image Network Model for Brain Tumor Classification Using Reconstructed Microwave Brain (RMB) Images.

Biosensors
Computerized brain tumor classification from the reconstructed microwave brain (RMB) images is important for the examination and observation of the development of brain disease. In this paper, an eight-layered lightweight classifier model called micr...