AIMC Topic: Machine Learning

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ML-UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper.

Physiological reports
The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution of urine spot patterns on filter paper with software remains problematic due to inter-laboratory di...

Research on Prediction model of Carotid-Femoral Pulse Wave Velocity: Based on Machine Learning Algorithm.

Journal of clinical hypertension (Greenwich, Conn.)
Carotid-femoral pulse wave velocity (cf-PWV) is an important but difficult to obtain measure of arterial stiffness and an independent predictor of cardiovascular events and all-cause mortality. The objective of this study was to develop a predictive ...

Machine Learning-Based Rapid Prediction of Torsional Performance of Personalized Peripheral Artery Stent.

International journal for numerical methods in biomedical engineering
The complex mechanical environment of peripheral arteries makes stents with poor torsional performance more prone to fracture, and stent fracture is considered a precursor to in-stent restenosis (ISR). Therefore, studying the torsional performance of...

Predicting Pharmacokinetics in Rats Using Machine Learning: A Comparative Study Between Empirical, Compartmental, and PBPK-Based Approaches.

Clinical and translational science
A successful drug needs to combine several properties including high potency and good pharmacokinetic (PK) properties to sustain efficacious plasma concentration over time. To estimate required doses for preclinical animal efficacy models or for the ...

Towards artificial intelligence application in pain medicine.

Recenti progressi in medicina
Pain is a complex, multidimensional experience involving significant challenges in both diagnosis and management. While acute pain serves as a critical warning mechanism, chronic pain encompasses intricate biological, psychological, and social compon...

The machine learning-based prediction of the sound pressure level from pathological and healthy speech signals.

The Journal of the Acoustical Society of America
Vocal intensity is quantified by sound pressure level (SPL). The SPL can be measured by either using a sound level meter or by comparing the energy of the recorded speech signal with the energy of the recorded calibration tone of a known SPL. Neither...

Machine Learning-Based Discovery of a Novel Noncovalent MurA Inhibitor as an Antibacterial Agent.

Chemical biology & drug design
The bacterial cell wall is crucial for maintaining the integrity of bacterial cells. UDP-N-acetylglucosamine 1-carboxyethylene transferase (MurA) is an important enzyme involved in bacterial cell wall synthesis. Therefore, it is an important target f...

An Integrated Fuzzy Neural Network and Topological Data Analysis for Molecular Graph Representation Learning and Property Forecasting.

Molecular informatics
Within a recent decade, graph neural network (GNN) has emerged as a powerful neural architecture for various graph-structured data modelling and task-driven representation learning problems. Recent studies have highlighted the remarkable capabilities...

Forestwalk: A Machine Learning Workflow Brings New Insights Into Posture and Balance in Rodent Beam Walking.

The European journal of neuroscience
The beam walk is widely used to study coordination and balance in rodents. While the task has ethological validity, the main endpoints of "foot slip counts" and "time to cross" are prone to human-rater variability and offer limited sensitivity and sp...