AIMC Topic: Algorithms

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Spectral integrated neural networks (SINNs) for solving forward and inverse dynamic problems.

Neural networks : the official journal of the International Neural Network Society
This study introduces an innovative neural network framework named spectral integrated neural networks (SINNs) to address both forward and inverse dynamic problems in three-dimensional space. In the SINNs, the spectral integration technique is utiliz...

Dynamic MRI interpolation in temporal direction using an unsupervised generative model.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
PURPOSE: Cardiac cine magnetic resonance imaging (MRI) is an important tool in assessing dynamic heart function. However, this technique requires long acquisition time and long breath holds, which presents difficulties. The aim of this study is to pr...

Optimizing Real-Time MI-BCI Performance in Post-Stroke Patients: Impact of Time Window Duration on Classification Accuracy and Responsiveness.

Sensors (Basel, Switzerland)
Brain-computer interfaces (BCIs) are promising tools for motor neurorehabilitation. Achieving a balance between classification accuracy and system responsiveness is crucial for real-time applications. This study aimed to assess how the duration of ti...

Predicting overall survival in anaplastic thyroid cancer using machine learning approaches.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Anaplastic thyroid carcinoma (ATC) is a highly aggressive and lethal thyroid cancer subtype with a poor prognosis. Recent advancements in machine learning (ML) have the potential to improve survival predictions. This study aimed to develop a...

A review of machine learning methods for non-invasive blood pressure estimation.

Journal of clinical monitoring and computing
Blood pressure is a very important clinical measurement, offering valuable insights into the hemodynamic status of patients. Regular monitoring is crucial for early detection, prevention, and treatment of conditions like hypotension and hypertension,...

Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Unplanned reoperation (URO) after surgery adversely affects the quality of life and prognosis of patients undergoing anterior resection for rectal cancer. This study aims to meet the urgent need for reliable predictive tools by developing...

The next revolution in computational simulations: Harnessing AI and quantum computing in molecular dynamics.

Current opinion in structural biology
The integration of artificial intelligence, machine learning and quantum computing into molecular dynamics simulations is catalyzing a revolution in computational biology, improving the accuracy and efficiency of simulations. This review describes th...

AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.

European radiology
OBJECTIVES: The assessment of lumbar central canal stenosis (LCCS) is crucial for diagnosing and planning treatment for patients with low back pain and neurogenic pain. However, manual assessment methods are time-consuming, variable, and require axia...

Optimized deep maxout for crowd anomaly detection: A hybrid optimization-based model.

Network (Bristol, England)
Monitoring Surveillance video is really time-consuming, and the complexity of typical crowd behaviour in crowded situations makes this even more challenging. This has sparked a curiosity about computer vision-based anomaly detection. This study intro...