Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda

Y Kumar, A Koul, R Singla, MF Ijaz - Journal of ambient intelligence and …, 2023 - Springer
Artificial intelligence can assist providers in a variety of patient care and intelligent health
systems. Artificial intelligence techniques ranging from machine learning to deep learning …

Machine learning-based coronary artery disease diagnosis: A comprehensive review

R Alizadehsani, M Abdar, M Roshanzamir… - Computers in biology …, 2019 - Elsevier
Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often
leads to a heart attack. It annually causes millions of deaths and billions of dollars in …

A new machine learning technique for an accurate diagnosis of coronary artery disease

M Abdar, W Książek, UR Acharya, RS Tan… - Computer methods and …, 2019 - Elsevier
Background and objective Coronary artery disease (CAD) is one of the commonest diseases
around the world. An early and accurate diagnosis of CAD allows a timely administration of …

[PDF][PDF] Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals

P Pławiak, UR Acharya - Neural Comput. Appl, 2020 - researchgate.net
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …

Improved machine learning-based predictive models for breast cancer diagnosis

A Rasool, C Bunterngchit, L Tiejian, MR Islam… - International journal of …, 2022 - mdpi.com
Breast cancer death rates are higher than any other cancer in American women. Machine
learning-based predictive models promise earlier detection techniques for breast cancer …

Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals

T Tuncer, S Dogan, P Pławiak, UR Acharya - Knowledge-Based Systems, 2019 - Elsevier
Electrocardiography (ECG) is widely used for arrhythmia detection nowadays. The machine
learning methods with signal processing algorithms have been used for automated …

A new nested ensemble technique for automated diagnosis of breast cancer

M Abdar, M Zomorodi-Moghadam, X Zhou… - Pattern Recognition …, 2020 - Elsevier
Nowadays, breast cancer is reported as one of most common cancers amongst women.
Early detection of this cancer is an essential to aid in informing subsequent treatments. This …

Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring

P Pławiak, M Abdar, UR Acharya - Applied Soft Computing, 2019 - Elsevier
In the recent decades, credit scoring has become a very important analytical resource for
researchers and financial institutions around the world. It helps to boost both profitability and …

LDA–GA–SVM: improved hepatocellular carcinoma prediction through dimensionality reduction and genetically optimized support vector machine

L Ali, I Wajahat, N Amiri Golilarz, F Keshtkar… - Neural Computing and …, 2021 - Springer
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 …

Software-based prediction of liver disease with feature selection and classification techniques

J Singh, S Bagga, R Kaur - Procedia Computer Science, 2020 - Elsevier
Today's health care is very important aspect for every human, so there is a need to provide
medical services that are easily available to everyone. In this paper, the main focus is to …