AI Medical Compendium Topic

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Models, Biological

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Multimodal Emotion Evaluation: A Physiological Model for Cost-Effective Emotion Classification.

Sensors (Basel, Switzerland)
Emotional responses are associated with distinct body alterations and are crucial to foster adaptive responses, well-being, and survival. Emotion identification may improve peoples' emotion regulation strategies and interaction with multiple life con...

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis.

Journal of visualized experiments : JoVE
Glomerular cell death is a pathological feature of myeloperoxidase anti neutrophil cytoplasmic antibody associated vasculitis (MPO-AAV). Extracellular deoxyribonucleic acid (ecDNA) is released during different forms of cell death including apoptosis,...

Unsupervised generative and graph representation learning for modelling cell differentiation.

Scientific reports
Using machine learning techniques to build representations from biomedical data can help us understand the latent biological mechanism of action and lead to important discoveries. Recent developments in single-cell RNA-sequencing protocols have allow...

Direct Comparison of Total Clearance Prediction: Computational Machine Learning Model versus Bottom-Up Approach Using In Vitro Assay.

Molecular pharmaceutics
The in vitro-in vivo extrapolation (IVIVE) approach for predicting total plasma clearance (CL) has been widely used to rank order compounds early in discovery. More recently, a computational machine learning approach utilizing physicochemical descrip...

Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks.

Scientific reports
Comorbidities such as anemia or hypertension and physiological factors related to exertion can influence a patient's hemodynamics and increase the severity of many cardiovascular diseases. Observing and quantifying associations between these factors ...

Radiomics in neuro-oncology: Basics, workflow, and applications.

Methods (San Diego, Calif.)
Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients with brain tumors for routine clinical purposes and the resulting number of imaging parameters have substantially increased. Consequently, a timely and...

Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

PloS one
Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transplantation, is crucial for patient's well-being and for successful management of the condition. In thi...

Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron.

Computational and mathematical methods in medicine
Coronavirus (COVID-19) is a highly infectious disease that has captured the attention of the worldwide public. Modeling of such diseases can be extremely important in the prediction of their impact. While classic, statistical, modeling can provide sa...

Mangrove forest classification and aboveground biomass estimation using an atom search algorithm and adaptive neuro-fuzzy inference system.

PloS one
BACKGROUND: Advances in earth observation and machine learning techniques have created new options for forest monitoring, primarily because of the various possibilities that they provide for classifying forest cover and estimating aboveground biomass...