AIMC Topic: Neural Networks, Computer

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Deep transfer learning-based decoder calibration for intracortical brain-machine interfaces.

Computers in biology and medicine
Intracortical brain-machine interfaces (iBMIs) aim to establish a communication path between the brain and external devices. However, in the daily use of iBMIs, the non-stationarity of recorded neural signals necessitates frequent recalibration of th...

A novel artificial intelligence-based methodology to predict non-specific response to treatment.

Psychiatry research
Non-specific response to treatment (NSRT) is the primary contributor to the failure of randomized clinical trials in major depressive disorder (MDD). The objective of this study is to develop artificial neural network (ANN) models to predict the indi...

Fine-Tuning Deep Learning Model for Quantitative Knee Joint Mapping With MR Fingerprinting and Its Comparison to Dictionary Matching Method: Fine-Tuning Deep Learning Model for Quantitative MRF.

NMR in biomedicine
Magnetic resonance fingerprinting (MRF), as an emerging versatile and noninvasive imaging technique, provides simultaneous quantification of multiple quantitative MRI parameters, which have been used to detect changes in cartilage composition and str...

Artificial intelligence classifies surgical technical skills in simulated laparoscopy: a pilot study.

Surgical endoscopy
OBJECTIVE: To develop a computer algorithm for the automatic classification of basic surgical skills in laparoscopy. The ability to objectively assess the operative skills of trainees would be invaluable for the success of competency-based medical ed...

High-Performance Computing-Based Brain Tumor Detection Using Parallel Quantum Dilated Convolutional Neural Network.

NMR in biomedicine
In the healthcare field, brain tumor causes irregular development of cells in the brain. One of the popular ways to identify the brain tumor and its progression is magnetic resonance imaging (MRI). However, existing methods often suffer from high com...

ICPPNet: A semantic segmentation network model based on inter-class positional prior for scoliosis reconstruction in ultrasound images.

Journal of biomedical informatics
OBJECTIVE: Considering the radiation hazard of X-ray, safer, more convenient and cost-effective ultrasound methods are gradually becoming new diagnostic approaches for scoliosis. For ultrasound images of spine regions, it is challenging to accurately...

Advances in artificial intelligence for diabetes prediction: insights from a systematic literature review.

Artificial intelligence in medicine
Diabetes mellitus (DM), a prevalent metabolic disorder, has significant global health implications. The advent of machine learning (ML) has revolutionized the ability to predict and manage diabetes early, offering new avenues to mitigate its impact. ...

Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models.

Artificial intelligence in medicine
A recent analysis of common stroke risk prediction models showed that performance differs between Black and White subgroups, and that applying standard machine learning methods does not reduce these disparities. There have been calls in the clinical ...

Joint high-resolution feature learning and vessel-shape aware convolutions for efficient vessel segmentation.

Computers in biology and medicine
Clear imagery of retinal vessels is one of the critical shreds of evidence in specific disease diagnosis and evaluation, including sophisticated hierarchical topology and plentiful-and-intensive capillaries. In this work, we propose a new topology- a...

Factors influencing the estimation of phacoemulsification procedure time in cataract surgery: Analysis using neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Realistic and accurate estimation of the surgery duration is one of the key factors influencing the optimization of hospital work and, consequently, the planning and management of the budget. In the present study, the author...