Machine Learning Approach for Classification of Sickle Cell Anemia in Teenagers Based on Bayesian Network
In this study, we employed a Bayesian network approach for the classification of sickle cell
anemia in teenagers based on their medical data. Sickle cell anemia is a hereditary blood …
anemia in teenagers based on their medical data. Sickle cell anemia is a hereditary blood …
[PDF][PDF] Comprehensive Impact Assessment of Intrusion Detection and Mitigation Strategies Using Support Vector Machine Classification
Cybersecurity remains a paramount concern in today's interconnected digital space,
necessitating continual evaluation and refinement of intrusion detection and mitigation …
necessitating continual evaluation and refinement of intrusion detection and mitigation …
[PDF][PDF] Customized Web Application for Addressing Language ModelMisalignment through Reinforcement Learning from HumanFeedback
A Uwah, A Edet - World Journal of Innovation And Modern …, 2024 - iiardjournals.org
Recent years have seen tremendous progress in the field of artificial intelligence, which has
sparked the creation of cutting-edge tools like OpenAI ChatGPT. The OpenAI GPT-3 family of …
sparked the creation of cutting-edge tools like OpenAI ChatGPT. The OpenAI GPT-3 family of …
[PDF][PDF] Security Framework for Detection of Denial of Service (DoS) Attack on Virtual Private Networks for Efficient Data Transmission
This study delves into the problem of detecting Denial-of-Service (DoS) attacks on Virtual
Private Network (VPN) servers and the detrimental impact of such attacks on network …
Private Network (VPN) servers and the detrimental impact of such attacks on network …
[PDF][PDF] Machine Learning Model for Adverse Drug Reaction Detection Based on Naive Bayes and XGBoost Algorithm
Adverse drug effects, commonly referred to as adverse drug reactions (ADRs), represent
undesirable and unintended responses to medications or pharmaceutical products when …
undesirable and unintended responses to medications or pharmaceutical products when …
[PDF][PDF] Machine Learning Enabled System for Health Impact Assessment of Soft Drink Consumption Using Ensemble Learning Technique
Soft drinks, often high in added sugars, have raised significant public health concerns due to
their association with adverse health effects such as obesity, type 2 diabetes, and …
their association with adverse health effects such as obesity, type 2 diabetes, and …
[PDF][PDF] DATA-DRIVEN FRAMEWORK FOR CLASSIFICATION AND MANAGEMENT OF START-UP RISK FOR HIGH INVESTMENT RETURNS
This research explores the classification of startup risks to achieve high investment returns
using Random Forest Regression. The study aims to identify and predict potential risks …
using Random Forest Regression. The study aims to identify and predict potential risks …
Machine Learning Approach for Classification of Cyber Threats Actors in Web Region
In the interconnected scape of today's internet, the dark web emerges as a concealed point,
covering a myriad of illicit activities that pose substantial cybersecurity risks. This study …
covering a myriad of illicit activities that pose substantial cybersecurity risks. This study …
[PDF][PDF] INTELLIGENT SYSTEM FOR DETECTION OF COPYRIGHT-PROTECTED DATA FOR ENHANCED DATA SECURITY
In the digital era, the proliferation of digital content has intensified concerns over intellectual
property rights infringement, highlighting the need for robust copyright protection solutions …
property rights infringement, highlighting the need for robust copyright protection solutions …
[PDF][PDF] Optimizing Hypertension Risk Classification through Machine Learning
Hypertension, a universal health concern worldwide, significantly contributes to
cardiovascular disease and premature mortality. This study explores the classification of …
cardiovascular disease and premature mortality. This study explores the classification of …