[HTML][HTML] Speech emotion recognition using machine learning—A systematic review

S Madanian, T Chen, O Adeleye, JM Templeton… - Intelligent systems with …, 2023 - Elsevier
Speech emotion recognition (SER) as a Machine Learning (ML) problem continues to
garner a significant amount of research interest, especially in the affective computing …

Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter …

L Hussain - Cognitive neurodynamics, 2018 - Springer
Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the
brain. The research reveals that brain activity is monitored through electroencephalogram …

Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies

L Hussain, A Ahmed, S Saeed, S Rathore… - Cancer …, 2018 - content.iospress.com
Prostate is a second leading causes of cancer deaths among men. Early detection of cancer
can effectively reduce the rate of mortality caused by Prostate cancer. Due to high and …

Speech emotion recognition research: an analysis of research focus

MB Mustafa, MAM Yusoof, ZM Don… - International Journal of …, 2018 - Springer
This article analyses research in speech emotion recognition (“SER”) from 2006 to 2017 in
order to identify the current focus of research, and areas in which research is lacking. The …

Detecting brain tumor using machines learning techniques based on different features extracting strategies

L Hussain, S Saeed, IA Awan, A Idris… - Current Medical …, 2019 - ingentaconnect.com
Background: Brain tumor is the leading cause of death worldwide. It is obvious that the
chances of survival can be increased if the tumor is identified and properly classified at an …

Regression analysis for detecting epileptic seizure with different feature extracting strategies

L Hussain, S Saeed, A Idris, IA Awan… - Biomedical …, 2019 - degruyter.com
Due to the excitability of neurons in the brain, a neurological disorder is produced known as
epilepsy. The brain activity of patients suffering from epilepsy is monitored through …

Smart cities-based improving atmospheric particulate matters prediction using chi-square feature selection methods by employing machine learning techniques

HA Mengash, L Hussain, H Mahgoub… - Applied Artificial …, 2022 - Taylor & Francis
Particulate matter is emitted from diverse sources and affect the human health very badly.
Dust particles exposure from the stated environment can affect our heart and lungs very …

[PDF][PDF] Does employee envy trigger the positive outcomes at workplace? A study of upward social comparison, envy and employee performance

MH Khan, A Noor - Journal of Global Business Insights, 2020 - academia.edu
The purpose of this research was to investigate the outcomes of envy in the workplace and
the moderating role of perceived organizational support. Data was collected from 270 …

Detecting congestive heart failure by extracting multimodal features with synthetic minority oversampling technique (SMOTE) for imbalanced data using robust …

L Hussain, KJ Lone, IA Awan, AA Abbasi… - Waves in Random and …, 2022 - Taylor & Francis
The incidence of congestive heart failure (CHF) is approximately 10 per 1000 for Americans
over the age of 65 years. The dynamics of CHF are highly complex, nonlinear, and temporal …

Arrhythmia detection by extracting hybrid features based on refined Fuzzy entropy (FuzEn) approach and employing machine learning techniques

L Hussain, W Aziz, S Saeed, IA Awan… - Waves in Random …, 2020 - Taylor & Francis
Cardiac arrhythmias are disturbances in the rhythm of the heart manifested by irregularity or
by abnormally fast rates ('tachycardia') or abnormally slow rates ('bradycardias'). In the past …