The Background
Methods/Technology
Applications
100

Will AI replace doctors in the near future? (True or False)

False

100

Which of the following is a primary application of machine learning in medical imaging?

  • A) Predicting weather patterns

  • B) Diagnosing diseases from images (e.g., X-rays, MRIs)

  • C) Editing genetic code in embryos

  • D) Designing new surgical tools

  • B) Diagnosing diseases from images (e.g., X-rays, MRIs)

100

True or False: The purpose of Natural Language Processing is to increase the workload on physicians

False

200

List any one advantage of implementing AI in medicine.

1. Help Reduce workload

2. Efficient in automating tasks

3. Saves money

4. Reduce errors

200

Which of the following statements reflects the main reason for the recent "hype" of AI in healthcare?

A) AI can replace all human doctors and medical staff.

B) AI models promise to improve diagnostics, treatment personalization, and patient outcomes.

C) AI is a cheaper alternative to traditional clinical training.

D) AI can fully automate patient consultations.



B) AI models promise to improve diagnostics, treatment personalization, and patient outcomes.

200

Which two specific components of NLP are used to understand and generate human-like text?

  1. Chatgpt

  2. Natural Language Understanding (NLU) and Natural Language Generation (NLG).

  3. Natural Language Comprehension (NLC) and Natural Language Speaking (NLS)

  4. None of the above

  • Answer: Natural Language Understanding (NLU) and Natural Language Generation (NLG).

300

What are the common applications of AI?

1. Robotics

2. Healthcare

3. E-commerce

(Any other answer that makes sense counts)

300

Which of the following machine learning techniques is most often associated with unsupervised learning in medical research?

  • A) Linear regression

  • B) K-means clustering

  • C) Decision trees

D) Support vector machines


  • B) K-means clustering

300

How can Natural Language Processing (NLP) assist in reducing physician burnout in clinical settings?

  1. Allowing them to take on multiple patients at a given time

  2. By creating more work for them

  3. By automating documentation and analyzing electronic health records, thus reducing the administrative workload on physicians.

  4. All of the above

Answer: By automating documentation and analyzing electronic health records, thus reducing the administrative workload on physicians.

400

Name a significant growth driver of the AI in healthcare market.

1. Significant decrement in the number of physicians

2. Rising prevalence of neurological disorders

400

What is one of the primary purposes of model deployment in a clinical setting?

  • A) To showcase machine learning applications to stakeholders

  • B) To implement the trained model into real-world clinical workflows

  • C) To improve model accuracy by testing it on new patient data

D) To simplify the data preprocessing steps


  • B) To implement the trained model into real-world clinical workflows

400

Topic Modelling, used in health research is the process of:

  1. Identifying and categorizing topics or themes within a collection of documents

  2. Analyzing drug interactions with genes, biomarkers and environment

  3. Sorting patients into cohorts for clinical trials

  4. Analyzing patient emotions and creating sentiment scores

  • Answer: Identifying and categorizing topics or themes within a collection of documents

500

Name any two influential moments in the development of AI in medicine (with respect to the background presentation)

1. 1950s-1980s - Machine Learning Origins

2. 1980s - Medical Imaging Boom

3. 1996 - Data Privacy Regulations

4. 2003 - Human Genome Project Completion

5. 2020 - COVID-19 Pandemic

500

Explain the process by which NLP works and creates structured representation from clinical notes

Unstructured data (clinical notes) - OCR - Words token - Semantic, syntactic and pragmatic analysis - using medical databases and terminologies - structured representation used for diagnosis



500

What ethical concerns must be addressed when implementing Natural Language Processing in health care?

Ensuring patient data privacy, mitigating biases in model outcomes, obtaining informed consent, and establishing liability frameworks 

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