AI for Neurological Disorder Progression Prediction and Treatment Optimization
Supervisor: Dr. Sumaira Kausar, Professor
Campus/School/Dept: BUIC(CoE-AI)
RAC Approved Supervisor for Research Areas: Computer Vision, Machine Learning, Medical Imaging, Disease Diagnosis
Supervisory Record:
- PhD Produced: 0
- PhD Enrolled: 2
- MS/MPhil Produced: 26
- MS/MPhil Enrolled: 1
Topic Brief Description:
This research focuses on leveraging artificial intelligence, particularly machine learning and reinforcement learning, to predict the progression of neurological disorders such as Alzheimer’s, Parkinson’s, or multiple sclerosis. The goal is to analyze longitudinal data, including medical records, imaging results, genetic information, and lifestyle factors, to model disease trajectories. By accurately forecasting how a disorder is likely to progress in individual patients, AI can provide valuable insights into the timing and severity of symptoms. Furthermore, reinforcement learning algorithms can be used to identify and recommend optimal, personalized treatment plans that balance efficacy, side effects, and quality of life.This approach not only empowers clinicians with predictive tools for proactive interventions but also supports patients in managing their conditions more effectively. Additionally, the integration of AI can enhance clinical trial design by stratifying patients based on predicted disease progression, ensuring more targeted and efficient therapeutic testing.
Research Objectives/Deliverables:
- To develop and validate AI-driven models for accurately predicting the progression of neurological disorders and optimizing personalized treatment strategies to improve patient outcomes and quality of life.
Research Questions:
- How can artificial intelligence, particularly machine learning and reinforcement learning, be utilized to model the progression of neurological disorders and recommend personalized, evidence-based treatment plans tailored to individual patient profiles?
Candidate’s Eligibility Profile:
- The applicant must have an MS/MPhil/Equivalent degree in electrical engineering with CGPA >0. Besides, applicants must have a strong background in artificial intelligence, machine learning and related fields.
- Experience with programming languages such as Python is required. Candidates should thrive in an international environment and have excellent communication skills to actively contribute to team research efforts.
- Proficiency in spoken and written English is essential. We value independence and responsibility while promoting teamwork and collaboration among colleagues.