AIMC Topic: Algorithms

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Automated Diagnosis of Chest X-Ray for Early Detection of COVID-19 Disease.

Computational and mathematical methods in medicine
In March 2020, the World Health Organization announced the COVID-19 pandemic, its dangers, and its rapid spread throughout the world. In March 2021, the second wave of the pandemic began with a new strain of COVID-19, which was more dangerous for som...

A Deep Learning-Based Classification Method for Different Frequency EEG Data.

Computational and mathematical methods in medicine
In recent years, the research on electroencephalography (EEG) has focused on the feature extraction of EEG signals. The development of convenient and simple EEG acquisition devices has produced a variety of EEG signal sources and the diversity of the...

A novel MADM algorithm for landfill site selection based on q-rung orthopair probabilistic hesitant fuzzy power Muirhead mean operator.

PloS one
With the rapid development of economy and the acceleration of urbanization, the garbage produced by urban residents also increases with the increase of population. In many big cities, the phenomenon of "garbage siege" has seriously affected the devel...

Interpretable machine learning for genomics.

Human genetics
High-throughput technologies such as next-generation sequencing allow biologists to observe cell function with unprecedented resolution, but the resulting datasets are too large and complicated for humans to understand without the aid of advanced sta...

Elucidating factors influencing machine learning algorithm prediction in spasticity assessment: a prospective observational study.

Computer methods in biomechanics and biomedical engineering
The Machine Learning Model (MLM) has garnered popularity in rehabilitation, ranging from developing algorithms in outcome prediction, prognostication, and training artificial intelligence. High-quality data plays a critical role in algorithm developm...

Utility of a Deep Learning Algorithm for Detection of Reticular Opacity on Chest Radiography in Patients With Interstitial Lung Disease.

AJR. American journal of roentgenology
Deep learning has been heavily explored for pulmonary nodule detection on chest radiographs. Detection of reticular opacity in interstitial lung disease (ILD) is challenging and may also benefit from a deep learning algorithm (DLA). The purpose of ...

Artificial Intelligence in Toxicological Pathology: Quantitative Evaluation of Compound-Induced Follicular Cell Hypertrophy in Rat Thyroid Gland Using Deep Learning Models.

Toxicologic pathology
Digital pathology has recently been more broadly deployed, fueling artificial intelligence (AI) application development and more systematic use of image analysis. Here, two different AI models were developed to evaluate follicular cell hypertrophy in...

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after r...

Machine Learning Based Identification of Microseismic Signals Using Characteristic Parameters.

Sensors (Basel, Switzerland)
Microseismic monitoring system is one of the effective means to monitor ground stress in deep mines. The accuracy and speed of microseismic signal identification directly affect the stability analysis in rock engineering. At present, manual identific...

Design of a Data Glove for Assessment of Hand Performance Using Supervised Machine Learning.

Sensors (Basel, Switzerland)
The large number of poststroke recovery patients poses a burden on rehabilitation centers, hospitals, and physiotherapists. The advent of rehabilitation robotics and automated assessment systems can ease this burden by assisting in the rehabilitation...