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 …
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 …
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 …
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 …
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 …
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 …
[PDF][PDF] Improving SVM classification performance on unbalanced student graduation time data using SMOTE
Abstract—Student graduation accuracy is one of the indicators of the success of higher
education institutions in carrying out the teaching and learning process and as a component …
education institutions in carrying out the teaching and learning process and as a component …
Handling imbalanced datasets through optimum-path forest
In the last decade, machine learning-based approaches became capable of performing a
wide range of complex tasks sometimes better than humans, demanding a fraction of the …
wide range of complex tasks sometimes better than humans, demanding a fraction of the …
Context-aware big data quality assessment: a scoping review
The term data quality refers to measuring the fitness of data regarding the intended usage.
Poor data quality leads to inadequate, inconsistent, and erroneous decisions that could …
Poor data quality leads to inadequate, inconsistent, and erroneous decisions that could …
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 …