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Nighat Bibi

Student

Project Title

Explainable Arficial Intelligence (XAI) in Healthcare

Project Description

The brain is the body’s command centre; it controls the function of each organ. The effects of any disruption in the brain can be disastrous. Therefore, it is essential to find brain illnesses early before they deteriorate. Brain tumour, Alzheimer’s disease, Autism, and other common brain conditions must be recognized in the early stages; otherwise, the outcome may be worse.

Brain tumour occurs because of the abnormal development of cells in the brain. It is one of the significant reasons for death in adults around the globe. Millions of deaths can be prevented through the early detection of brain tumours. MRI images are considered helpful for detecting and localising tumours.

Alzheimer’s disease is a degenerative neurological condition that causes the brain to atrophy, which causes the brain to shrink and the brain cells to die. It affects people between the ages of 30 to middle 60. Alzheimer’s disease affects 5.8 million people in the United States who are 65 years or older. It is a typical dementia cause. Sadly, Alzheimer’s is incurable and can cause death and a severe loss of brain function. Therefore, it must be detected early and treated.

Autism spectrum disorder (ASD) is a neurological disorder that impacts how people connect with others, communicate, learn, and conduct. It first manifests in early childhood, evolves throughout life, and needs to be caught early to speed up therapy and recovery. In addition, medical brain imaging techniques may be used to identify these impairments.

There are different biomedical image techniques. However, MRI images provide clear images of a brain that can help an accurate diagnosis of brain diseases.

Many AI-based approaches already exist for diagnosing brain diseases; however, the black-box approaches are not considered more reliable in the healthcare field, so the explainability of AI-based models is crucial in disease diagnosis. Explainable Artificial Intelligence supports researchers in justifying their model with transparent results that lead to trustworthiness for clinicians, doctors, and patients.

Objectives:

We aim to provide explainability of the diagnosis of brain diseases, i.e., Brain tumours, Alzheimer’s Disease, and Autism, from MRI images. The fundamental reasons behind this research are:

  • Provide accurate, fast, and early detection of brain diseases
  • Provide a transparent/trustworthy/explainable diagnosis of brain diseases (why and how our model predicts these results)
  • Detect more than one type of brain disease from MRI images
  • Proof that AI-based models are trustworthy for the diagnosis of diseases from MRI images

Approach

In this research, machine learning and deep learning models will be employed to diagnose brain diseases (Brain tumours, Alzheimer’s disease, and Autism) with high accuracy from MRI images and XAI methods (like SHAP, LIME, and LRP) will be used to provide transparency of the models and reason behind their decision (output).