[HTML][HTML] A systematic review of applications of machine learning and other soft computing techniques for the diagnosis of tropical diseases

K Attai, Y Amannejad, M Vahdat Pour, O Obot… - Tropical Medicine and …, 2022 - mdpi.com
This systematic literature aims to identify soft computing techniques currently utilized in
diagnosing tropical febrile diseases and explore the data characteristics and features used …

Emerging Technologies for Enhancing Robust Cybersecurity Measures for Business Intelligence in Healthcare 5.0

AR Sakhawat, A Fatima, S Abbas, M Ahmad… - … to Protect Business …, 2024 - igi-global.com
Healthcare 5.0 represents the next phase in healthcare evolution. It aims to harness the
creativity and expertise of healthcare professionals, integrating them with efficient …

Comparative Analysis of Customer Loan Approval Prediction using Machine Learning Algorithms

P Tumuluru, LR Burra, M Loukya… - … and Smart Energy …, 2022 - ieeexplore.ieee.org
In today's increasingly competitive market, estimating the risk involved in a loan application
is one of the most crucial challenges for banks' survival and profitability. The banks receive …

[HTML][HTML] Comparison of machine learning algorithms used for skin cancer diagnosis

M Bistroń, Z Piotrowski - Applied Sciences, 2022 - mdpi.com
The paper presents a comparison of automatic skin cancer diagnosis algorithms based on
analyses of skin lesions photos. Two approaches are presented: the first one is based on the …

Twitter spam detection using naïve bayes classifier

KU Santoshi, SS Bhavya, YB Sri… - 2021 6th international …, 2021 - ieeexplore.ieee.org
Twitter is the well liked social media platform that has over 300 million monthly users which
post 500 million tweets per day. This is the main reason why spammers use Twitter for their …

Machine learning techniques for anomaly detection in smart healthcare

M Kavitha, P Srinivas, PSL Kalyampudi… - 2021 Third …, 2021 - ieeexplore.ieee.org
Anomaly detection is a vital research problem among the different domains intrusion
detection, fraud detection, device health monitoring, fault data detection, event detection in …

APMWMM: Approach to Probe Malware on Windows Machine using Machine Learning

P Tumuluru, LR Burra, MVV Reddy… - … on Applied Artificial …, 2022 - ieeexplore.ieee.org
The popularity of Windows gadgets is growing as well and are more defenseless to malware
attacks. This venture proposes a modern imaging strategy to identify malware viably by …

An improved early detection method of autism spectrum anarchy using euclidean method

V Deepak, SJJ Thangaraj… - … on I-SMAC (IoT in Social …, 2020 - ieeexplore.ieee.org
Autistic Spectrum Disorder (ASD) is one of the mental disorders that affect the acquisition of
linguistic, communication, cognitive, and social skills and abilities. Regardless of being …

Detection of COVID disease from CT scan images using CNN model

P Tumuluru, P Srinivas… - … and Smart Energy …, 2022 - ieeexplore.ieee.org
The world is affected by an existential global health crisis called the COVID-19 pandemic.
Countries like the United States, India and Russia are still having and gaining positive …

Dpmlt: Diabetes prediction using machine learning techniques

P Tumuluru, LR Burra, KK Sushanth… - … on Electronics and …, 2022 - ieeexplore.ieee.org
One of the most frequent chronic diseases is diabetes, which can afflict anyone, regardless
of age. When the glucose or sugar level is too high, several diseases attack. Diabetes …