A comprehensive review of recent advances in artificial intelligence for dentistry e-health
Artificial intelligence has made substantial progress in medicine. Automated dental imaging
interpretation is one of the most prolific areas of research using AI. X-ray and infrared …
interpretation is one of the most prolific areas of research using AI. X-ray and infrared …
Handling imbalanced medical datasets: review of a decade of research
Abstract Machine learning and medical diagnostic studies often struggle with the issue of
class imbalance in medical datasets, complicating accurate disease prediction and …
class imbalance in medical datasets, complicating accurate disease prediction and …
Automatic cardiac arrhythmia classification using residual network combined with long short-term memory
Diagnosis and classification of arrhythmia, which is associated with abnormal electrical
activities in the heart, are critical for clinical treatments. Previous studies focused on the …
activities in the heart, are critical for clinical treatments. Previous studies focused on the …
[HTML][HTML] Predicting lung cancer survival based on clinical data using machine learning: A review
FA Altuhaifa, KT Win, G Su - Computers in Biology and Medicine, 2023 - Elsevier
Abstract Machine learning has gained popularity in predicting survival time in the medical
field. This review examines studies utilizing machine learning and data-mining techniques to …
field. This review examines studies utilizing machine learning and data-mining techniques to …
Text mining and emotion classification on monkeypox Twitter dataset: A deep learning-natural language processing (NLP) approach
Emotion classification has become a valuable tool in analyzing text and emotions people
express in response to events or crises, particularly on social media and other online …
express in response to events or crises, particularly on social media and other online …
Imbalanced classification methods for student grade prediction: a systematic literature review
Student success is essential for improving the higher education system student outcome.
One way to measure student success is by predicting students' performance based on their …
One way to measure student success is by predicting students' performance based on their …
Data-driven corrosion inhibition efficiency prediction model incorporating 2D–3D molecular graphs and inhibitor concentration
Following the construction of a dataset of cross-category corrosion inhibitors at different
concentrations based on 1241 data from 184 research papers, a performance prediction …
concentrations based on 1241 data from 184 research papers, a performance prediction …
Classification of COVID-19 from tuberculosis and pneumonia using deep learning techniques
L Venkataramana, DVV Prasad, S Saraswathi… - Medical & Biological …, 2022 - Springer
Deep learning provides the healthcare industry with the ability to analyse data at exceptional
speeds without compromising on accuracy. These techniques are applicable to healthcare …
speeds without compromising on accuracy. These techniques are applicable to healthcare …
Predicting open education competency level: A machine learning approach
G Ibarra-Vazquez, MS Ramírez-Montoya… - Heliyon, 2023 - cell.com
This article aims to study open education competency data through machine learning
models to determine whether models can be built on decision rules using the features from …
models to determine whether models can be built on decision rules using the features from …
Differentiating interstitial lung diseases from other respiratory diseases using electronic nose technology
IG van der Sar, MS Wijsenbeek, GJ Braunstahl… - Respiratory …, 2023 - Springer
Introduction Interstitial lung disease (ILD) may be difficult to distinguish from other respiratory
diseases due to overlapping clinical presentation. Recognition of ILD is often late, causing …
diseases due to overlapping clinical presentation. Recognition of ILD is often late, causing …