Enhancing Precision Oncology: Artificial Intelligence in the Identification of Cancer Molecular Subtype

Cancer is a top cause of mortality around the globe, presenting a significant challenge to global health. Cancer is a highly complex genomic disease, with each type exhibiting unique genetic and molecular changes at different stages, necessitating the need for personalized treatment plans. However, the diversity of cancer is not limited to different types, it also varies within cancers from the same organ. Therefore, identifying the molecular subtype of cancer is a vital step in both cancer research and clinical treatments. It will play a key role in boosting the effectiveness of existing therapies and guiding the development of future treatments, with the ultimate goal of increasing patient survival rates. The objective of this research is to utilize artificial intelligence (AI) in healthcare by introducing an innovative method that employs deep learning to identify cancer molecular subtypes through the analysis of multiple large omics datasets. This method aims to identify cancer subtypes with unprecedented precision, offering a significant leap towards personalized medicine. This research aligns with the United Nations Sustainable Development Goal No. 3, Good Health and Well-being, contributing to global efforts in combating cancer and highlighting the role of technology-driven solutions in tackling major health challenges.

Publication Details

Journal
Scholarship at UWindsor (University of Windsor)
Published
2025-03-26
Primary Topic
Magnetic confinement fusion research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Precision Oncology: Artificial Intelligence in the Identification of Cancer Molecular Subtype

Scholarship at UWindsor (University of Windsor)
Magnetic confinement fusion research
article

Enhancing Precision Oncology: Artificial Intelligence in the Identification of Cancer Molecular Subtype

article en

Abstract

Cancer is a top cause of mortality around the globe, presenting a significant challenge to global health. Cancer is a highly complex genomic disease, with each type exhibiting unique genetic and molecular changes at different stages, necessitating the need for personalized treatment plans. However, the diversity of cancer is not limited to different types, it also varies within cancers from the same organ. Therefore, identifying the molecular subtype of cancer is a vital step in both cancer research and clinical treatments. It will play a key role in boosting the effectiveness of existing therapies and guiding the development of future treatments, with the ultimate goal of increasing patient survival rates. The objective of this research is to utilize artificial intelligence (AI) in healthcare by introducing an innovative method that employs deep learning to identify cancer molecular subtypes through the analysis of multiple large omics datasets. This method aims to identify cancer subtypes with unprecedented precision, offering a significant leap towards personalized medicine. This research aligns with the United Nations Sustainable Development Goal No. 3, Good Health and Well-being, contributing to global efforts in combating cancer and highlighting the role of technology-driven solutions in tackling major health challenges.

Scholarship at UWindsor (University of Windsor)
Partnerships for the goals
Openalex Percentile: Top 54%
Magnetic confinement fusion research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Enhancing Precision Oncology: Artificial Intelligence in the Identification of Cancer Molecular Subtype · Scholarship at UWindsor (University of Windsor) (2025) | TGRS Research Map | TGRS