AIMC Topic: Machine Learning

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[Artificial intelligence: An introduction for clinicians].

Revue des maladies respiratoires
Artificial intelligence (AI) is a growing field that has the potential to transform many areas of society, including healthcare. For a physician, it is important to understand the basics of AI and its potential applications in medicine. AI refers to ...

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review.

Archives of toxicology
The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ensure safe application on living organisms. Artificial intelligence (AI) and machine learning (MI) can be used to analyze and interpret large amounts of...

Stimulus classification with electrical potential and impedance of living plants: comparing discriminant analysis and deep-learning methods.

Bioinspiration & biomimetics
The physiology of living organisms, such as living plants, is complex and particularly difficult to understand on a macroscopic, organism-holistic level. Among the many options for studying plant physiology, electrical potential and tissue impedance ...

Artificial Intelligence Screening of Medical School Applications: Development and Validation of a Machine-Learning Algorithm.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: To explore whether a machine-learning algorithm could accurately perform the initial screening of medical school applications.

The promise and peril of interactive embodied agents for studying non-verbal communication: a machine learning perspective.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
In face-to-face interactions, parties rapidly react and adapt to each other's words, movements and expressions. Any science of face-to-face interaction must develop approaches to hypothesize and rigorously test mechanisms that explain such interdepen...

Ensemble Learning, Deep Learning-Based and Molecular Descriptor-Based Quantitative Structure-Activity Relationships.

Molecules (Basel, Switzerland)
A deep learning-based quantitative structure-activity relationship analysis, namely the molecular image-based DeepSNAP-deep learning method, can successfully and automatically capture the spatial and temporal features in an image generated from a thr...

Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care.

World journal of emergency surgery : WJES
Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can be trained based on datasets to make predictions. The increasing sophistication of AI has created new opportunities to apply these algorithms within ...

Automated detection of schizophrenia using deep learning: a review for the last decade.

Physiological measurement
Schizophrenia (SZ) is a devastating mental disorder that disrupts higher brain functions like thought, perception, etc., with a profound impact on the individual's life. Deep learning (DL) can detect SZ automatically by learning signal data character...