DELTA DIALOG

Alzheimer's and Machine Learning - with Sara Moein and Emir Mustafa Isler

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Overview: In this episode of the Delta Dialog, we delve into the significant impact of AI in healthcare, particularly focusing on disease prediction, diagnosis, and treatment.

Key Points:

1. AI in Alzheimer's Disease:

  • Use of Deep Neural Networks (DNNs) in differentiating between mild and severe Alzheimer's cases through brain imaging.
    • Steps involved in data acquisition, preprocessing, feature extraction, and model validation.

      • 2. Machine Learning Models in Alzheimer's Diagnosis:

      • Enhancing accuracy and speed compared to traditional methods.
        • Ability to analyze large, complex datasets including medical records, genetic information, and brain imaging.

          • 3. Addressing Bias in Machine Learning Models:

          • Techniques like cross-validation to ensure model accuracy and fairness.
            • Importance of validating and testing models with unseen data to eliminate biases.

              • 4. Machine Learning in Drug Development:

              • Accelerating the discovery and development of new drugs.
                • Predicting disease progression and treatment responses.
                  • Personalized medicine and evaluating drug efficacy using clinical trial data.

                    • 5. Genetic Associations and Disease:

                    • Identifying hidden associations between genetic defects and diseases like Alzheimer's.
                      • Integration of genomic, phenotypic, and environmental data.
                        • The role of feature engineering, supervised and unsupervised learning in understanding genetic profiles.

                          • Key Takeaways:

                          • AI and machine learning are revolutionizing the field of healthcare by improving diagnostic accuracy, speeding up drug development, and providing personalized treatment options.
                            • Techniques like DNNs and supervised/unsupervised learning are essential in managing and understanding complex diseases like Alzheimer's.
                              • Addressing bias and validating models are critical steps in ensuring the reliability of AI tools in clinical settings.
                                • ...more
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                                DELTA DIALOGBy Emir Mustafa Isler