From Pixels to Prognosis: Artificial Intelligence and Machine Learning Models in Brain Tumour Mutation Prediction

Authors

  • Quratulain Tariq Department of Neurosurgery, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan
  • Eisha Abid Ali Medical Student, University College of Medicine and Dentistry, Lahore, Pakistan,
  • Saad bin Anis Department of Neurosurgery, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan
  • Irfan Yousaf Department of Neurosurgery, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan
  • Ahmer Nasir Baig Department of Neurosurgery, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan
  • Muhammad Shahzad Shamim Department of Neurosurgery, Aga Khan University Hospital, Karachi, Pakistan

DOI:

https://doi.org/10.47391/JPMA.25-05

Abstract

Brain tumours are a leading cause of death and disability,
impacting individuals across all ages, genders, and
ethnicities. They are primarily diagnosed using MRI but a
precise diagnosis is dependent on the molecular biology
of the tumour studied on the pathological specimen.
Artificial intelligence and machine learning are forging
new paths through diagnostic obstacles, offering the
intriguing benefits of non-invasive diagnosis, pattern
recognition, and outcome prediction from imaging data.
Here, we present a literature review on the role of
machine learning in tumour mutations using imaging
alone.
Keywords: brain tumor, artificial intelligence, machine
learning, tumor mutation.

Published

2024-12-23

How to Cite

Quratulain Tariq, Eisha Abid Ali, Saad bin Anis, Irfan Yousaf, Ahmer Nasir Baig, & Muhammad Shahzad Shamim. (2024). From Pixels to Prognosis: Artificial Intelligence and Machine Learning Models in Brain Tumour Mutation Prediction. Journal of the Pakistan Medical Association, 75(1), 140–141. https://doi.org/10.47391/JPMA.25-05

Issue

Section

EVIDENCE BASED NEURO-ONCOLOGY

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