AIMC Topic: Algorithms

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Application of machine-learning models to predict the ganciclovir and valganciclovir exposure in children using a limited sampling strategy.

Antimicrobial agents and chemotherapy
Intravenous ganciclovir and oral valganciclovir display significant variability in ganciclovir pharmacokinetics, particularly in children. Therapeutic drug monitoring currently relies on the area under the concentration-time (AUC). Machine-learning (...

Quantitative assessment of human motion for health and rehabilitation: A novel fuzzy comprehensive evaluation approach.

SLAS technology
In the pursuit of advancing health and rehabilitation, the quintessence of human motion recognition technology has been underscored through its quantitative contributions to physical performance assessment. This research delineates the inception of a...

Predicting the Binding of Small Molecules to Proteins through Invariant Representation of the Molecular Structure.

Journal of chemical information and modeling
We present a computational scheme for predicting the ligands that bind to a pocket of a known structure. It is based on the generation of a general abstract representation of the molecules, which is invariant to rotations, translations, and permutati...

Integrating graph convolutional networks to enhance prompt learning for biomedical relation extraction.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: Biomedical relation extraction aims to reveal the relation between entities in medical texts. Currently, the relation extraction models that have attracted much attention are mainly to fine-tune the pre-trained language mode...

Interactive dual-stream contrastive learning for radiology report generation.

Journal of biomedical informatics
Radiology report generation automates diagnostic narrative synthesis from medical imaging data. Current report generation methods primarily employ knowledge graphs for image enhancement, neglecting the interpretability and guiding function of the kno...

Machine Learning Based Abnormal Gait Classification with IMU Considering Joint Impairment.

Sensors (Basel, Switzerland)
Gait analysis systems are critical for assessing motor function in rehabilitation and elderly care. This study aimed to develop and optimize an abnormal gait classification algorithm considering joint impairments using inertial measurement units (IMU...

GaitKeeper: An AI-Enabled Mobile Technology to Standardize and Measure Gait Speed.

Sensors (Basel, Switzerland)
Gait speed is increasingly recognized as an important health indicator. However, gait analysis in clinical settings often encounters inconsistencies due to methodological variability and resource constraints. To address these challenges, GaitKeeper u...

Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.

BMC medical imaging
Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominently found in diabetic patients. The early identification of DR/DME grades facilitates the devising of an appropriate treatment plan, which ultimately ...

Development of predictive model for the neurological deterioration among mild traumatic brain injury patients using machine learning algorithms.

Neurosurgical review
BACKGROUND: Mild traumatic brain injury (mTBI) comprises a majority of traumatic brain injury (TBI) cases. While some mTBI would suffer neurological deterioration (ND) and therefore have poorer prognosis. This study was designed to develop the predic...

Convolutional neural network-based regression analysis to predict subnuclear chromatin organization from two-dimensional optical scattering signals.

Journal of biomedical optics
SIGNIFICANCE: Azimuth-resolved optical scattering signals obtained from cell nuclei are sensitive to changes in their internal refractive index profile. These two-dimensional signals can therefore offer significant insights into chromatin organizatio...