Artificial intelligence in surveillance, diagnosis, drug discovery and vaccine development against COVID-19

G Arora, J Joshi, RS Mandal, N Shrivastava, R Virmani… - Pathogens, 2021 - mdpi.com
As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-
confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic …

IoMT cloud-based intelligent prediction of breast cancer stages empowered with deep learning

SY Siddiqui, A Haider, TM Ghazal, MA Khan… - IEEE …, 2021 - ieeexplore.ieee.org
Breast cancer is often a fatal disease that has a substantial impact on the female mortality
rate. Rapidly spreading breast cancer is due to the abnormal growth of malignant cells in the …

Joint diagnosis of pneumonia, COVID-19, and tuberculosis from chest X-ray images: A deep learning approach

MS Ahmed, A Rahman, F AlGhamdi, S AlDakheel… - Diagnostics, 2023 - mdpi.com
Pneumonia, COVID-19, and tuberculosis are some of the most fatal and common lung
diseases in the current era. Several approaches have been proposed in the literature for the …

An IoMT‐Enabled Smart Healthcare Model to Monitor Elderly People Using Machine Learning Technique

MF Khan, TM Ghazal, RA Said, A Fatima… - Computational …, 2021 - Wiley Online Library
The Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast
health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many …

A review on machine learning approaches in identification of pediatric epilepsy

MIB Ahmed, S Alotaibi, S Dash, M Nabil… - SN computer science, 2022 - Springer
Epilepsy is the second most common neurological disease after Alzheimer. It is a disorder of
the brain which results in recurrent seizures. Though the epilepsy in general is considered …

A deep learning approach to intelligent fruit identification and family classification

NM Ibrahim, DGI Gabr, A Rahman, S Dash… - Multimedia Tools and …, 2022 - Springer
The deep learning techniques have been playing an important role in the identification and
classification problems such as diseases in medical science, marketing in the industry …

ZeVigilante: Detecting Zero‐Day Malware Using Machine Learning and Sandboxing Analysis Techniques

F Alhaidari, NA Shaib, M Alsafi… - Computational …, 2022 - Wiley Online Library
For the enormous growth and the hysterical impact of undocumented malicious software,
otherwise known as Zero-Day malware, specialized practices were joined to implement …

[PDF][PDF] A Neuro-Fuzzy Approach to Road Traffic Congestion Prediction.

M Gollapalli, D Musleh, N Ibrahim, MA Khan… - … , Materials & Continua, 2022 - academia.edu
The fast-paced growth of artificial intelligence applications provides unparalleled
opportunities to improve the efficiency of various systems. Such as the transportation sector …

Ensemble machine learning model to predict the waterborne syndrome

M Gollapalli - Algorithms, 2022 - mdpi.com
The COVID-19 epidemic has highlighted the significance of sanitization and maintaining
hygienic access to clean water to reduce mortality and morbidity cases worldwide. Diarrhea …

Ensemble learning based sustainable approach to carbonate reservoirs permeability prediction

DA Musleh, SO Olatunji, AA Almajed, AS Alghamdi… - Sustainability, 2023 - mdpi.com
Permeability is a crucial property that can be used to indicate whether a material can hold
fluids or not. Predicting the permeability of carbonate reservoirs is always a challenging and …