Analysis of Early Cancer Diagnosis Using Machine Learning
Date Issued
2024
Author(s)
Gjosheva, Marija
Bogoevski, Zlate
Velichkovska, Bojana
Efnusheva, Danijela
Abstract
Cancer is a group of diseases with similar symptoms, all involving
uncontrolled growth and reproduction of cells. With around 8 million deaths each
year, it is the second leading cause of death worldwide in developing countries
and the first in the developed world. In contemporary medicine, early cancer diagnosis for every known type is essential. Machine learning has the potential to
completely transform the process and increase the number of lives saved. In order
to make predictions, computers develop complex data models and search for patterns. Early cancer diagnosis could undergo a revolution because of machine
learning.
This research’s goal is to outline the issue surrounding cancer diagnoses in patients and all the difficulties they experience. A suitable strategy will be to model
the risk of cancer and patient outcomes given the growing trend of employing
machine learning technics in cancer research. A specific model has been developed that, if applied appropriately, can reduce the number of lost lives and, at the
same time, increase the number of individuals capable of coping with this disease. The results indicate that the created model can be used by professionals to
identify lung cancer with efficiency. If the prediction is accurate, the doctor may
be able to develop a better treatment plan and provide the patient with an early
diagnosis. The study's findings show that the number of patients has been rising
recently, yet early detection is crucial because it can help avert serious complications.
uncontrolled growth and reproduction of cells. With around 8 million deaths each
year, it is the second leading cause of death worldwide in developing countries
and the first in the developed world. In contemporary medicine, early cancer diagnosis for every known type is essential. Machine learning has the potential to
completely transform the process and increase the number of lives saved. In order
to make predictions, computers develop complex data models and search for patterns. Early cancer diagnosis could undergo a revolution because of machine
learning.
This research’s goal is to outline the issue surrounding cancer diagnoses in patients and all the difficulties they experience. A suitable strategy will be to model
the risk of cancer and patient outcomes given the growing trend of employing
machine learning technics in cancer research. A specific model has been developed that, if applied appropriately, can reduce the number of lost lives and, at the
same time, increase the number of individuals capable of coping with this disease. The results indicate that the created model can be used by professionals to
identify lung cancer with efficiency. If the prediction is accurate, the doctor may
be able to develop a better treatment plan and provide the patient with an early
diagnosis. The study's findings show that the number of patients has been rising
recently, yet early detection is crucial because it can help avert serious complications.