Machine learning integrated graphene oxide‐based diagnostics, drug delivery, analytical approaches to empower cancer diagnosis
Abstract Machine learning (ML) and nanotechnology interfacing are exploring opportunities
for cancer treatment strategies. To improve cancer therapy, this article investigates the …
for cancer treatment strategies. To improve cancer therapy, this article investigates the …
FocalNeXt: A ConvNeXt augmented FocalNet architecture for lung cancer classification from CT-scan images
Early and accurate diagnosis of lung cancer, a life-threatening disease, is critical to the
successful treatment of patients with the disease. On the other hand, it is well known that the …
successful treatment of patients with the disease. On the other hand, it is well known that the …
[HTML][HTML] Edge-cloud synergy for AI-enhanced sensor network data: A real-time predictive maintenance framework
K Sathupadi, S Achar, SV Bhaskaran, N Faruqui… - Sensors, 2024 - mdpi.com
Sensor networks generate vast amounts of data in real-time, which challenges existing
predictive maintenance frameworks due to high latency, energy consumption, and …
predictive maintenance frameworks due to high latency, energy consumption, and …
A novel IDS with a dynamic access control algorithm to detect and defend intrusion at IoT nodes
The Internet of Things (IoT) is the underlying technology that has enabled connecting daily
apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is …
apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is …
[HTML][HTML] A sco** review of deep learning approaches for lung cancer detection using chest radiographs and computed tomography scans
MN Nguyen - Biomedical Engineering Advances, 2024 - Elsevier
Lung cancer remains the most lethal cancer, primarily due to late diagnoses. Thus, early
detection of lung cancer is critical to improving patient outcomes. While conventional …
detection of lung cancer is critical to improving patient outcomes. While conventional …
[HTML][HTML] RAP-Optimizer: Resource-Aware Predictive Model for Cost Optimization of Cloud AIaaS Applications
Artificial Intelligence (AI) applications are rapidly growing, and more applications are joining
the market competition. As a result, the AI-as-a-service (AIaaS) model is experiencing rapid …
the market competition. As a result, the AI-as-a-service (AIaaS) model is experiencing rapid …
Prediction of Tuberculosis From Lung Tissue Images of Diversity Outbred Mice Using Jump Knowledge Based Cell Graph Neural Network
Tuberculosis (TB), primarily affecting the lungs, is caused by the bacterium Mycobacterium
tuberculosis and poses a significant health risk. Detecting acid-fast bacilli (AFB) in stained …
tuberculosis and poses a significant health risk. Detecting acid-fast bacilli (AFB) in stained …
Optimizing lung cancer prediction: leveraging Kernel PCA with dendritic neural models
U Arif, C Zhang, MW Chaudhary… - Computer Methods in …, 2024 - Taylor & Francis
Lung cancer is considered a cause of increased mortality rate due to delays in diagnostics.
There is an urgent need to develop an effective lung cancer prediction model that will help in …
There is an urgent need to develop an effective lung cancer prediction model that will help in …
Flamingo Search Sailfish Optimizer Based SqueezeNet for Detection of Breast Cancer Using MRI Images
Breast cancer with increased risk in women is identified with Breast Magnetic Resonance
Imaging (Breast MRI) and this helps in evaluating treatment therapies. Breast MRI is time …
Imaging (Breast MRI) and this helps in evaluating treatment therapies. Breast MRI is time …
[HTML][HTML] BankNet: Real-Time Big Data Analytics for Secure Internet Banking
K Sathupadi, S Achar, SV Bhaskaran… - Big Data and Cognitive …, 2025 - mdpi.com
The rapid growth of Internet banking has necessitated advanced systems for secure, real-
time decision making. This paper introduces BankNet, a predictive analytics framework …
time decision making. This paper introduces BankNet, a predictive analytics framework …