AI Medical Compendium Topic

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Demystifying food flavor: Flavor data interpretation through machine learning.

Food chemistry
Flavor data obtained from analytical techniques are vast and complex, which increases the difficulty of multi-factorial analysis. This study aims to provide a machine learning (ML)-based framework to interpret flavor data, exploiting four widely used...

A sustainable system for predicting appliance energy consumption based on machine learning.

Journal of environmental management
Nowadays, energy conservation is a top priority for sustainable societies, which focus on environmental and economic sustainability to address fossil fuel scarcity, climate change, and increasing environmental pollution. Therefore, planning for energ...

Machine learning approaches for assessing medication transfer to human breast milk.

Journal of pharmacokinetics and pharmacodynamics
The human milk/plasma (M/P) drug concentration ratio is crucial in pharmacology, especially for breastfeeding mothers undergoing treatment. It determines the extent to which drugs ingested by the mother pass into breast milk, potentially affecting th...

Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic Regression.

ACS nano
Optical spectroscopy, a noninvasive molecular sensing technique, offers valuable insights into material characterization, molecule identification, and biosample analysis. Despite the informativeness of high-dimensional optical spectra, their interpre...

A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides.

Scientific reports
Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) ...

Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients.

Scientific reports
The precise and efficient diagnosis of an individual's skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations ...

Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.

Scientific reports
Many people suffer from Parkinson's disease globally, a complicated neurological condition caused by the deficiency of dopamine, an organic chemical responsible for regulating movement in individuals. Patients with Parkinson face muscle stiffness or ...

Artificial neural networks applied to somatosensory evoked potentials for migraine classification.

The journal of headache and pain
BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity...

An effective PO-RSNN and FZCIS based diabetes prediction and stroke analysis in the metaverse environment.

Scientific reports
Chronic disease (CD) like diabetes and stroke impacts global healthcare extensively, and continuous monitoring and early detection are necessary for effective management. The Metaverse Environment (ME) has gained attention in the digital healthcare e...