AIMC Topic: Algorithms

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The Role of Artificial Intelligence and Machine Learning in Assisted Reproductive Technologies.

Obstetrics and gynecology clinics of North America
Artificial intelligence (AI) and machine learning, the form most commonly used in medicine, offer powerful tools utilizing the strengths of large data sets and intelligent algorithms. These systems can help to revolutionize delivery of treatments, ac...

An integrated modelling framework for multiple pollution source identification in surface water.

Journal of environmental management
Pollution source identification is vital in water safety management. An integrated simulation-optimization modelling framework comprising a process-based hydrodynamic water quality model, artificial neural network surrogate model and particle swarm o...

Predicting the therapeutic efficacy of AIT for asthma using clinical characteristics, serum allergen detection metrics, and machine learning techniques.

Computers in biology and medicine
Bronchial asthma is a prevalent non-communicable disease among children. The study collected clinical data from 390 children aged 4-17 years with asthma, with or without rhinitis, who received allergen immunotherapy (AIT). Combining these data, this ...

Deep learning imaging reconstruction of reduced-dose 40 keV virtual monoenergetic imaging for early detection of colorectal cancer liver metastases.

European journal of radiology
OBJECTIVE: To explore whether reduced-dose (RD) gemstone spectral imaging (GSI) and deep learning image reconstruction (DLIR) of 40 keV virtual monoenergetic image (VMI) enhanced the early detection and diagnosis of colorectal cancer liver metastases...

EQNAS: Evolutionary Quantum Neural Architecture Search for Image Classification.

Neural networks : the official journal of the International Neural Network Society
Quantum neural network (QNN) is a neural network model based on the principles of quantum mechanics. The advantages of faster computing speed, higher memory capacity, smaller network size and elimination of catastrophic amnesia make it a new idea to ...

A self-training algorithm based on the two-stage data editing method with mass-based dissimilarity.

Neural networks : the official journal of the International Neural Network Society
A self-training algorithm is a classical semi-supervised learning algorithm that uses a small number of labeled samples and a large number of unlabeled samples to train a classifier. However, the existing self-training algorithms consider only the ge...

A deep learning approach for transgender and gender diverse patient identification in electronic health records.

Journal of biomedical informatics
BACKGROUND: Although accurate identification of gender identity in the electronic health record (EHR) is crucial for providing equitable health care, particularly for transgender and gender diverse (TGD) populations, it remains a challenging task due...

An ensemble deep-learning approach for single-trial EEG classification of vibration intensity.

Journal of neural engineering
. Single-trial electroencephalography (EEG) classification is a promising approach to evaluate the cognitive experience associated with haptic feedback. Convolutional neural networks (CNNs), which are among the most widely used deep learning techniqu...

Machine learning in clinical practice: Evaluation of an artificial intelligence tool after implementation.

Emergency medicine Australasia : EMA
OBJECTIVE: Artificial intelligence (AI) has gradually found its way into healthcare, and its future integration into clinical practice is inevitable. In the present study, we evaluate the accuracy of a novel AI algorithm designed to predict admission...