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Artificial Intelligence-Driven Models for Predicting Prognosis in Non-Small Cell Lung Cancer in Egypt with a Global Comparison

Principal Investigator
Name
Nourhan Mohamed
Degrees
ph.D
Institution
Medical Research Institute
Position Title
PH.D candidate
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCOI-1748
Initial CDAS Request Approval
Nov 21, 2024
Title
Artificial Intelligence-Driven Models for Predicting Prognosis in Non-Small Cell Lung Cancer in Egypt with a Global Comparison
Summary
The potential of artificial intelligence (AI) in the field of healthcare lies in its capacity to analyze huge data that surpass human capabilities. This analytical ability enables the conversion of data into clinical knowledge, which can guide medical practitioners in making informed decisions and ultimately lead to improved patient outcomes. The objective is to decrease healthcare expenses while simultaneously enhancing patient contentment.
Artificial intelligence is used in machine learning, which enables frameworks to automatically accept and enhance information without overt adaptation. Machine learning focuses on enhancing PC programs that can take in information and figure things out by themselves.
To the best of our current understanding in the developing countries, there exists a discernible degree of efficacy pertaining to the implementation of artificial intelligence (AI) within the fields of oncology and cancer epidemiology. The Integration of AI algorithms and advanced computing techniques have provided researchers and clinicians with unparalleled opportunities to decipher complex datasets and extract valuable insights, which in turn have led to enhanced disease detection, more accurate diagnoses, and tailored treatment regimens. While further investigation is required to fully elucidate the extent of AI's potential within this domain, it is evident that the integration of AI technologies holds considerable promise for advancing our understanding of cancer and improving patient outcomes.
Aims

The aim of this study is to predict the progression of cancer patients diagnosed with non-small cell lung cancer (NSCLC (in Egypt with a global comparison using machine learning and Artifial intelligence technology.

Collaborators

Supervision Committee:
Prof. Dr. Fayek Elkhwsky
Professor of Medical statistics
Department of Biomedical informatics and medical statistics
Medical Research Institute, Alexandria University

Prof. Dr. Waleed Arafat
Professor Oncology
Faculty of Medicine, Alexandria University

Assoc. Prof. Marwan Torki
Associate professor department of Computer and system engineering
Faculty of Engineering, Alexandria University

Dr. Ehsan Akram Daghedy
Lecturer of Medical statistics
Department of Biomedical informatics and medical statistics
Medical Research Institute, Alexandria University