Osteoporosis

Effective and efficient neural networks for spike inference from calcium imaging.

Calcium imaging provides advantages in monitoring large populations of neuronal activities simultaneously. However, it lacks the signal quality provided by neural spike recording in traditional electrophysiology. To address this issue, we developed a supervised data-driven approach to extract spike information from calcium signals. We propose the ENS (effective and efficient neural networks for sp...

Realizing Molecular Machine Learning through Communications for Biological AI: Future Directions and Challenges.

Artificial Intelligence (AI) and Machine Learning (ML) are weaving their way into the fabric of society, where they are playing a crucial role in numerous facets of our lives. As we witness the increased deployment of AI and ML in various types of devices, we benefit from their use into energy-efficient algorithms for low powered devices. In this paper, we investigate a scale and medium that is fa...

Robot-Assisted Kyphoplasty versus Fluoroscopy-Assisted Kyphoplasty: A Meta-Analysis of Postoperative Outcomes.

Osteoporotic vertebral compression fractures are the most common manifestation of osteoporosis. Percutaneous kyphoplasty (PKP) can lead to both pain i...

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent...

Fuzzy-based models' performance on qualitative and quantitative land suitability evaluation for cotton cultivation in Sarayan County, South Khorasan Province, Iran.

Using appropriate models in the land use planning process will help increase the accuracy and precision of decisions made by designers. The aim of thi...

Optimization of biocementation responses by artificial neural network and random forest in comparison to response surface methodology.

In this article, the optimization of the specific urease activity (SUA) and the calcium carbonate (CaCO) using microbially induced calcite precipitati...

Deep learning for automatic mandible segmentation on dental panoramic x-ray images.

Many studies in the last decades have correlated mandible bone structure with systemic diseases like osteoporosis. Mandible segmentation, as well as s...

Discovery of ANO1 Inhibitors based on Machine learning and molecule docking simulation approaches.

Calcium-activated chloride channels (CaCCs) are chloride channels that are regulated according to intracellular calcium ion concentrations. The channe...

Advances in materials-based therapeutic strategies against osteoporosis.

Osteoporosis is caused by the disruption in homeostasis between bone formation and bone resorption. Conventional management of osteoporosis involves s...

Interpretable Deep-Learning Approaches for Osteoporosis Risk Screening and Individualized Feature Analysis Using Large Population-Based Data: Model Development and Performance Evaluation.

BACKGROUND: Osteoporosis is one of the diseases that requires early screening and detection for its management. Common clinical tools and machine-lear...

Prediction of Coronary Artery Calcium Using Deep Learning of Echocardiograms.

BACKGROUND: Coronary artery calcification (CAC), often assessed by computed tomography (CT), is a powerful marker of coronary artery disease that can ...

Acute Intraoperative Hyperkalemia During Robot-Assisted Radical Cystectomy: A Case Report.

A 50-year-old man with muscle-invasive bladder cancer was scheduled for a robotic radical cystectomy. Four hours into the surgery, his electrocardiogr...

Performance of 1-mm non-gated low-dose chest computed tomography using deep learning-based noise reduction for coronary artery calcium scoring.

OBJECTIVE: To investigate performance of 1-mm, sharp kernel, low-dose chest computed tomography (LDCT) for coronary artery calcium scoring (CACS) usin...

Impact of deep learning image reconstructions (DLIR) on coronary artery calcium quantification.

BACKGROUND: Deep learning image reconstructions (DLIR) have been recently introduced as an alternative to filtered back projection (FBP) and iterative...

Prediction Models for Identifying Ion Channel-Modulating Peptides via Knowledge Transfer Approaches.

Ion channels, which can be modulated by peptides, are promising drug targets for neurological, metabolic, and cardiovascular disorders. Because it is ...

Volumetric imaging of fast cellular dynamics with deep learning enhanced bioluminescence microscopy.

Bioluminescence microscopy is an appealing alternative to fluorescence microscopy, because it does not depend on external illumination, and consequent...

The geometry of representational drift in natural and artificial neural networks.

Neurons in sensory areas encode/represent stimuli. Surprisingly, recent studies have suggested that, even during persistent performance, these represe...

A deep learning framework for inference of single-trial neural population dynamics from calcium imaging with subframe temporal resolution.

In many areas of the brain, neural populations act as a coordinated network whose state is tied to behavior on a millisecond timescale. Two-photon (2p...

Predicting the risk of osteoporosis in older Vietnamese women using machine learning approaches.

Osteoporosis contributes significantly to health and economic burdens worldwide. However, the development of osteoporosis-related prediction tools has...

Machine Learning Techniques Outperform Conventional Statistical Methods in the Prediction of High Risk QTc Prolongation Related to a Drug-Drug Interaction.

In clinical practice, many drug therapies are associated with prolongation of the QT interval. In literature, estimation of the risk of prescribing dr...