[HTML][HTML] Amalgamation of Blockchain with resource-constrained IoT devices for Healthcare applications–State of Art, Challenges and Future Directions
P Hegde, PKR Maddikunta - … Journal of Cognitive Computing in Engineering, 2023 - Elsevier
Healthcare is an emerging sector with the integration of emerging technologies aiming to
improve Quality of Life of an individual through various medical services. Most of the …
improve Quality of Life of an individual through various medical services. Most of the …
Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning
Cancer is a fatal disease caused by a combination of genetic diseases and a variety of
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
A dependable hybrid machine learning model for network intrusion detection
Network intrusion detection systems (NIDSs) play an important role in computer network
security. There are several detection mechanisms where anomaly-based automated …
security. There are several detection mechanisms where anomaly-based automated …
Diabetes prediction using machine learning and explainable AI techniques
I Tasin, TU Nabil, S Islam… - Healthcare Technology …, 2023 - Wiley Online Library
Globally, diabetes affects 537 million people, making it the deadliest and the most common
non‐communicable disease. Many factors can cause a person to get affected by diabetes …
non‐communicable disease. Many factors can cause a person to get affected by diabetes …
[HTML][HTML] A risk assessment and prediction framework for diabetes mellitus using machine learning algorithms
Diabetes disease seriously threatens people's health and is becoming more common
nowadays. Diabetes Mellitus (DM) is a condition caused by high blood sugar levels …
nowadays. Diabetes Mellitus (DM) is a condition caused by high blood sugar levels …
[HTML][HTML] A robust hybrid machine learning model for Bengali cyber bullying detection in social media
Social networking platforms give users countless opportunities to share information,
collaborate, and communicate positively. The same platform can be extended to a fabricated …
collaborate, and communicate positively. The same platform can be extended to a fabricated …
[HTML][HTML] Automatic COVID-19 prediction using explainable machine learning techniques
S Solayman, SA Aumi, CS Mery, M Mubassir… - International Journal of …, 2023 - Elsevier
The coronavirus is considered this century's most disruptive catastrophe and global concern.
This disease has prompted extreme social, psychological and economic impacts affecting …
This disease has prompted extreme social, psychological and economic impacts affecting …
[HTML][HTML] DeepCrop: Deep learning-based crop disease prediction with web application
MM Islam, MAA Adil, MA Talukder… - Journal of Agriculture …, 2023 - Elsevier
Agriculture plays a significant role in every nation's economy by producing crops. Plant
disease identification is one of the most important aspects of maintaining an agriculturally …
disease identification is one of the most important aspects of maintaining an agriculturally …
A hybrid dependable deep feature extraction and ensemble-based machine learning approach for breast cancer detection
Breast cancer is a prevalent and life-threatening disease that requires effective detection
and diagnosis methods to improve patient outcomes. Deep learning (DL) and machine …
and diagnosis methods to improve patient outcomes. Deep learning (DL) and machine …
[HTML][HTML] Comparison of multiclass classification techniques using dry bean dataset
Background The application of classsification methods through multivariate and machine
learning techniques has enormous significance in agricultural sector. It is vital to classify …
learning techniques has enormous significance in agricultural sector. It is vital to classify …