Machine learning for dementia prediction: a systematic review and future research directions
Abstract Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully
provided automated solutions to numerous real-world problems. Healthcare is one of the …
provided automated solutions to numerous real-world problems. Healthcare is one of the …
Machine learning for the diagnosis of Parkinson's disease: a review of literature
Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and
assessment of clinical signs, including the characterization of a variety of motor symptoms …
assessment of clinical signs, including the characterization of a variety of motor symptoms …
[Retracted] Machine Learning‐Based Automated Diagnostic Systems Developed for Heart Failure Prediction Using Different Types of Data Modalities: A Systematic …
A Javeed, SU Khan, L Ali, S Ali… - … Methods in Medicine, 2022 - Wiley Online Library
One of the leading causes of deaths around the globe is heart disease. Heart is an organ
that is responsible for the supply of blood to each part of the body. Coronary artery disease …
that is responsible for the supply of blood to each part of the body. Coronary artery disease …
LDA–GA–SVM: improved hepatocellular carcinoma prediction through dimensionality reduction and genetically optimized support vector machine
Hepatocellular carcinoma (HCC) is a common type of liver cancer worldwide. Patients with
HCC have rare chances of survival. The chances of survival increase, if the cancer is …
HCC have rare chances of survival. The chances of survival increase, if the cancer is …
Heart risk failure prediction using a novel feature selection method for feature refinement and neural network for classification
Diagnosis of heart disease is a difficult job, and researchers have designed various
intelligent diagnostic systems for improved heart disease diagnosis. However, low heart …
intelligent diagnostic systems for improved heart disease diagnosis. However, low heart …
MMDD-Ensemble: A Multimodal Data–Driven Ensemble Approach for Parkinson's Disease Detection
Parkinson's disease (PD) is the second most common neurological disease having no
specific medical test for its diagnosis. In this study, we consider PD detection based on …
specific medical test for its diagnosis. In this study, we consider PD detection based on …
Parkinson's disease diagnosis in cepstral domain using MFCC and dimensionality reduction with SVM classifier
Parkinson's disease (PD) is one of the most common and serious neurological diseases.
Impairments in voice have been reported to be the early biomarkers of the disease. Hence …
Impairments in voice have been reported to be the early biomarkers of the disease. Hence …
An approach based on mutually informed neural networks to optimize the generalization capabilities of decision support systems developed for heart failure prediction
L Ali, SAC Bukhari - Irbm, 2021 - Elsevier
Available clinical methods for heart failure (HF) diagnosis are expensive and require a high-
level of experts intervention. Recently, various machine learning models have been …
level of experts intervention. Recently, various machine learning models have been …
[Retracted] A Clinical Decision Support System (CDSS) for Unbiased Prediction of Caesarean Section Based on Features Extraction and Optimized Classification
A Javeed, L Ali, A Mohammed Seid… - Computational …, 2022 - Wiley Online Library
Nowadays, caesarean section (CS) is given preference over vaginal birth and this trend is
rapidly rising around the globe, although CS has serious complications such as pregnancy …
rapidly rising around the globe, although CS has serious complications such as pregnancy …
[Retracted] An Effective and Lightweight Deep Electrocardiography Arrhythmia Recognition Model Using Novel Special and Native Structural Regularization …
Recently, cardiac arrhythmia recognition from electrocardiography (ECG) with deep learning
approaches is becoming popular in clinical diagnosis systems due to its good prognosis …
approaches is becoming popular in clinical diagnosis systems due to its good prognosis …