AI Medical Compendium Topic

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Estimation of drug exposure by machine learning based on simulations from published pharmacokinetic models: The example of tacrolimus.

Pharmacological research
We previously demonstrated that Machine learning (ML) algorithms can accurately estimate drug area under the curve (AUC) of tacrolimus or mycophenolate mofetil (MMF) based on limited information, as well as or even better than maximum a posteriori Ba...

A model for obstructive sleep apnea detection using a multi-layer feed-forward neural network based on electrocardiogram, pulse oxygen saturation, and body mass index.

Sleep & breathing = Schlaf & Atmung
PURPOSE: To develop and evaluate a model for obstructive sleep apnea (OSA) detection using an artificial neural network (ANN) based on the combined features of body mass index (BMI), electrocardiogram (ECG), and pulse oxygen saturation (SpO2).

A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Bio Systems
Tolerance to stress conditions is vital for organismal survival, including bacteria under specific environmental conditions, antibiotics, and other perturbations. Some studies have described common modulation and shared genes during stress response t...

QSAR Models for Active Substances against Using Disk-Diffusion Test Data.

Molecules (Basel, Switzerland)
is a Gram-negative bacillus included among the six "ESKAPE" microbial species with an outstanding ability to "escape" currently used antibiotics and developing new antibiotics against it is of the highest priority. Whereas minimum inhibitory concent...

Predictive model for the 5-year survival status of osteosarcoma patients based on the SEER database and XGBoost algorithm.

Scientific reports
Osteosarcoma is the most common bone malignancy, with the highest incidence in children and adolescents. Survival rate prediction is important for improving prognosis and planning therapy. However, there is still no prediction model with a high accur...

A machine learning approach to personalized dose adjustment of lamotrigine using noninvasive clinical parameters.

Scientific reports
The pharmacokinetic variability of lamotrigine (LTG) plays a significant role in its dosing requirements. Our goal here was to use noninvasive clinical parameters to predict the dose-adjusted concentrations (C/D ratio) of LTG based on machine learnin...

MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer.

Scientific reports
Neoadjuvant chemo-radiotherapy (CRT) followed by total mesorectal excision (TME) represents the standard treatment for patients with locally advanced (≥ T3 or N+) rectal cancer (LARC). Approximately 15% of patients with LARC shows a complete response...

Machine-learning model led design to experimentally test species thermal limits: The case of kissing bugs (Triatominae).

PLoS neglected tropical diseases
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic areas using macro-climatic variables; however, micro-habitats can buffer or exacerbate the influence of macro-climatic variables, requiring links betwe...

Hands-on training about overfitting.

PLoS computational biology
Overfitting is one of the critical problems in developing models by machine learning. With machine learning becoming an essential technology in computational biology, we must include training about overfitting in all courses that introduce this techn...

Biped Walking Based on Stiffness Optimization and Hierarchical Quadratic Programming.

Sensors (Basel, Switzerland)
The spring-loaded inverted pendulum model is similar to human walking in terms of the center of mass (CoM) trajectory and the ground reaction force. It is thus widely used in humanoid robot motion planning. A method that uses a velocity feedback cont...