Supervised machine learning models for liver disease risk prediction

E Dritsas, M Trigka - Computers, 2023 - mdpi.com
The liver constitutes the largest gland in the human body and performs many different
functions. It processes what a person eats and drinks and converts food into nutrients that …

Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques

B Khan, R Naseem, MA Shah, K Wakil… - Journal of …, 2021 - Wiley Online Library
Software defect prediction (SDP) in the initial period of the software development life cycle
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …

An empirical evaluation of machine learning techniques for chronic kidney disease prophecy

B Khan, R Naseem, F Muhammad, G Abbas… - IEEE Access, 2020 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) implies that the human kidneys are harmed and unable to
blood filter in the manner which they should. The disease is designated “chronic” in light of …

Chronic kidney disease prediction using machine learning algorithms and the important attributes for the detection

G Shukla, G Dhuriya, SK Pillai… - 2023 IEEE IAS Global …, 2023 - ieeexplore.ieee.org
In the modern world, chronic kidney disease has become one of the most hazardous
diseases. CKD is a condition in which the kidney cannot perform the proper filtering of the …

Performance assessment of classification algorithms on early detection of liver syndrome

R Naseem, B Khan, MA Shah, K Wakil… - Journal of …, 2020 - Wiley Online Library
In the recent era, a liver syndrome that causes any damage in life capacity is exceptionally
normal everywhere throughout the world. It has been found that liver disease is exposed …

Investigating tree family machine learning techniques for a predictive system to unveil software defects

R Naseem, B Khan, A Ahmad, A Almogren… - …, 2020 - Wiley Online Library
Software defects prediction at the initial period of the software development life cycle
remains a critical and important assignment. Defect prediction and correctness leads to the …

Application of biochemical tests and machine learning techniques to diagnose and evaluate liver disease

S Akter, HU Shekhar… - … in Bioscience and …, 2021 - journal.article2publish.com
Background: The liver function tests (LFTs) remain one of the most commonly employed
clinical measures for the diagnosis of hepatobiliary disease. LFTs sometimes referred to as …

[PDF][PDF] Machine learning-based models for magnetic resonance imaging (MRI)-based brain tumor classification

AA Asiri, B Khan, F Muhammad… - Intell. Autom. Soft …, 2023 - cdn.techscience.cn
In the medical profession, recent technological advancements play an essential role in the
early detection and categorization of many diseases that cause mortality. The technique …

Analysis of tree-family machine learning techniques for risk prediction in software requirements

B Khan, R Naseem, I Alam, I Khan, H Alasmary… - IEEE …, 2022 - ieeexplore.ieee.org
Risk prediction is the most sensitive and critical activity in the Software Development Life
Cycle (SDLC). It might determine whether the project succeeds or fails. To increase the …

Detection COVID-19 using machine learning from blood tests

N Hany, N Atef, N Mostafa, S Mohamed… - 2021 International …, 2021 - ieeexplore.ieee.org
Coronavirus (COVID-19) is an infectious disease that spreads around the world lately. It is a
worldwide pandemic that affects mainly the lungs. It leads to huge risks as blood clotting …