AIMC Topic: Algorithms

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Prediction of gait trajectories based on the Long Short Term Memory neural networks.

PloS one
The forecasting of lower limb trajectories can improve the operation of assistive devices and minimise the risk of tripping and balance loss. The aim of this work was to examine four Long Short Term Memory (LSTM) neural network architectures (Vanilla...

Automatic detection of vessel structure by deep learning using intravascular ultrasound images of the coronary arteries.

PloS one
Intravascular ultrasound (IVUS) is a diagnostic modality used during percutaneous coronary intervention. However, specialist skills are required to interpret IVUS images. To address this issue, we developed a new artificial intelligence (AI) program ...

Deep learning-based detection of eosinophilic esophagitis.

Endoscopy
BACKGROUND: For eosinophilic esophagitis (EoE), a substantial diagnostic delay is still a clinically relevant phenomenon. Deep learning-based algorithms have demonstrated potential in medical image analysis. Here we establish a convolutional neuronal...

Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images.

Computer methods and programs in biomedicine
BACKGROUND: After the treatment of the patients with malignant lymphoma, there may persist lesions that must be labeled either as evolutive lymphoma requiring new treatments or as residual masses. We present in this work, a machine learning-based com...

Residual dense network for medical magnetic resonance images super-resolution.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: High-resolution magnetic resonance images (MRI) help experts to localize lesions and diagnose diseases, but it is difficult to obtain high-resolution MRI. Furthermore, image super-resolution technology based on deep learning...

Natural language processing for the assessment of cardiovascular disease comorbidities: The cardio-Canary comorbidity project.

Clinical cardiology
OBJECTIVE: Accurate ascertainment of comorbidities is paramount in clinical research. While manual adjudication is labor-intensive and expensive, the adoption of electronic health records enables computational analysis of free-text documentation usin...

Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search.

Journal of chemical information and modeling
Machine learning (ML) plays a growing role in the design and discovery of chemicals, aiming to reduce the need to perform expensive experiments and simulations. ML for such applications is promising but difficult, as models must generalize to vast ch...

Human biomechanics perspective on robotics for gait assistance: challenges and potential solutions.

Proceedings. Biological sciences
Technological advancements in robotic devices have the potential to transform human mobility through gait assistance. However, the integration of physical hardware and software control algorithms with users to assist with impaired gait poses several ...

Comparison of the Validity and Generalizability of Machine Learning Algorithms for the Prediction of Energy Expenditure: Validation Study.

JMIR mHealth and uHealth
BACKGROUND: Accurate solutions for the estimation of physical activity and energy expenditure at scale are needed for a range of medical and health research fields. Machine learning techniques show promise in research-grade accelerometers, and some e...