Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,491 to 1,500 of 6,930 articles

Deep learning framework for hourly air pollutants forecasting using encoding cyclical features across multiple monitoring sites in Beijing.

Scientific reports
Environmental managers and citizens alike are concerned with air quality. Early warning systems for air pollution are essential to prevent health issues and implement effective prevention strategies. This paper proposes a comprehensive, reliable syst... read more 

Schizophrenia detection from electroencephalogram signals using image encoding and wrapper-based deep feature selection approach.

Scientific reports
Schizophrenia is a persistent and serious mental illness that leads to distortions in cognition, perception, emotions, speech, self-awareness, and actions. Affecting about 1% of people worldwide, schizophrenia usually emerges in late adolescence or e... read more 

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG.

Scientific reports
Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges (IEDs). Clinical MEG analysis in epileptic patients traditionally relies on the visual identification of IEDs, which is time consuming and partially ... read more 

Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm.

Scientific reports
In the human body, the skin is the main organ. Nearly 30-70% of individuals globally have skin-related health issues, for whom efficient and effective analysis is essential. A general method dermatologists use for analyzing skin illnesses is dermosco... read more 

Deep learning based classification of tibio-femoral knee osteoarthritis from lateral view knee joint X-ray images.

Scientific reports
Design an effective deep learning-driven method to locate and classify the tibio-femoral knee joint space width (JSW) with respect to both anterior-posterior (AP) and lateral views. Compare the results and see how successfully a deep learning approac... read more 

A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.

Scientific reports
Discriminate deep vein thrombosis, one of the complications in early stroke patients, in order to assist in diagnosis. We have constructed a new method called ACWGAN by combining ACGAN and WGAN methods for data augmentation to to enhance the data of ... read more 

Comparing ChatGPT and validated questionnaires in assessing loneliness and online social support among college students: a cross-sectional study.

Scientific reports
The capability of ChatGPT to understand and generate human-readable text has prompted the investigation of its potential as mental health assessment tools. This study aims to explore the validity of ChatGPT in assessing loneliness and online social s... read more 

Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants.

Scientific reports
Congenital syphilis is a global public health issue, and its diagnostic complexity poses a challenge to early treatment. Fourier Transform Infrared Spectroscopy (FTIR) is a promising technological tool that facilitates the detection and diagnosis of ... read more 

Trees vs neural networks for enhancing tau lepton real-time selection in proton-proton collisions.

Scientific reports
This paper introduces supervised learning techniques for real-time selection (triggering) of hadronically decaying tau leptons in proton-proton colliders. By implementing traditional machine learning decision trees and advanced deep learning models, ... read more 

Detecting heavy trucks from mobile phone trajectories using image-based behavioral representations and deep learning models.

Scientific reports
This paper proposes an innovative methodology for detecting heavy trucks utilizing mobile phone data, addressing significant limitations inherent in traditional tracking methods, often characterized by high costs, intrusiveness, and incomplete data c... read more