In this review, we compiled convolutional neural network (CNN) methods which have the
potential to automate the manual, costly and error-prone processing of medical images. We …

The goal of this research is to create an ensemble deep learning model for Internet of Things
(IoT) applications that specifically target remote patient monitoring (RPM) by integrating long …

The survival rate of lung cancer relies significantly on how far the disease has spread when
it is detected, how it reacts to the treatment, the patient's overall health, and other factors …

As lung cancer has emerged as the top contributor to cancer-related fatalities, efficient and
precise diagnostic methods are essential for efficient diagnosis. This research introduces a …

World Health Organization (WHO) has identified depression as a significant contributor to
global disability, creating a complex thread in both public and private health …

Prompt diagnosis is crucial globally to save lives, underscoring the urgent need in light of
lung cancer's status as a leading cause of death. While CT scans serve as a primary …

The disease known as lung cancer, which is common and frequently deadly, starts in the
cells of the lungs and causes symptoms like exhaustion, chest pain, and persistent …

With a focus on user engagement, content distribution, sentiment analysis, and predictive
modeling, the study provides a thorough analysis of Twitter data. Using popular hashtags …

ABSTRACT Enhancing Medical Image Analysis with Convolutional Neural Networks: A
Paradigm Shift in Healthcare Diagnostics" presents a groundbreaking approach to medical …