AIMC Topic: Databases, Factual

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Machine Learning Analysis of Essential Oils from Cuban Plants: Potential Activity against Protozoa Parasites.

Molecules (Basel, Switzerland)
Essential oils (EOs) are a mixture of chemical compounds with a long history of use in food, cosmetics, perfumes, agricultural and pharmaceuticals industries. The main object of this study was to find chemical patterns between 45 EOs and antiprotozoa...

Machine learning methods to predict presence of residual cancer following hysterectomy.

Scientific reports
Surgical management for gynecologic malignancies often involves hysterectomy, often constituting the most common gynecologic surgery worldwide. Despite maximal surgical and medical care, gynecologic malignancies have a high rate of recurrence followi...

Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.

Scientific reports
Temporal dataset shift associated with changes in healthcare over time is a barrier to deploying machine learning-based clinical decision support systems. Algorithms that learn robust models by estimating invariant properties across time periods for ...

Machine learning-based prediction of critical illness in children visiting the emergency department.

PloS one
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...

Structure-aware siamese graph neural networks for encounter-level patient similarity learning.

Journal of biomedical informatics
Patient similarity learning has attracted great research interest in biomedical informatics. Correctly identifying the similarity between a given patient and patient records in the database could contribute to clinical references for diagnosis and me...

Research on Emotion Recognition of EEG Signal Based on Convolutional Neural Networks and High-Order Cross-Analysis.

Journal of healthcare engineering
Emotion recognition means the automatic identification of a human's emotional state by obtaining his/her physiological or nonphysiological signals. The EEG-based method is an effective mechanism, which is commonly used for the recognition of emotions...

Automated Cardioailment Identification and Prevention by Hybrid Machine Learning Models.

Computational and mathematical methods in medicine
Accurate prediction of cardiovascular disease is necessary and considered to be a difficult attempt to treat a patient effectively before a heart attack occurs. According to recent studies, heart disease is said to be one of the leading origins of de...

Epileptic Seizure Detection with Hybrid Time-Frequency EEG Input: A Deep Learning Approach.

Computational and mathematical methods in medicine
The precise detection of epileptic seizure helps to prevent the serious consequences of seizures. As the electroencephalogram (EEG) reflects the brain activity of patients effectively, it has been widely used in epileptic seizure detection in the pas...

Internet of Things with Deep Learning-Based Face Recognition Approach for Authentication in Control Medical Systems.

Computational and mathematical methods in medicine
Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant role in many applications, including medical and healthcare systems. It can help users in this field get an advantage in terms of enhanced touchless authe...

Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

Surgical endoscopy
BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant information in the endoscopy reporting system to facilitate data collection, which may be inaccurate...