1.Question 1What is precision medicine?1 pointA 'one size fits all’ approach to treatment and care of patients Anew drug to treat all diseases.A personalised approach to therapies, tailoring them to suit eachindividual. Anaccurate medical diagnosis. 2.Question 2 The ability to characterise individuals muchmore precisely allows us to identify key differences across human populationsand to act accordingly in healthcare provision – this is stratified healthcare. 1 pointTrueFalse3.Question 3What are the benefits of using data science inmedicine and healthcare? 1 pointIt canhelp identify the most effective treatments for a particular medicalcondition. Itcan help analyse patient records to identify certain individuals at risk of aparticular medical condition. Both of the above.None of the above. 4.Question 4Which of the following statements about the datascience process is correct?1 pointCleaning data is only rarely part of the datascience process.Data analysis is the final phase of the datascience process.The data science process is linear.The data science process may be repeated severaltimes throughout a project.5.Question 5Complete the following code, so as to get the type of b.123a = 10b = (0.2 * a) + 8# add your code hereRunResetWhat result do you get when running your code?1 pointintstrboolfloat6.Question 6The following code specifies a dictionary that maps patients to their doctors. Complete the code so as to get the doctor for Janet.123doctors = {"Susan" : "Dr Fox", "Janet" : "Dr Prentice", "Tommy" : "Dr Peng", "Jacques" : "Dr Prentice", "Margaret" : "Dr Peng"}doctors["Janet"] = "Dr Harrison"# add your code hereRunResetWho is Janet's doctor, based on the code output?1 pointTommyDr PrenticeDr PengDr Harrison7.Question 7The following code specifies a DataFrame that captures information about patients. What is the code for getting the shape of patients, and what is the output?Note that you can try this out in the Jupyter Notebook for "Python Basics Part 2".1 pointThe code is1patients.shapeThe output is (4, 5).The code is:1patients.shapeThe output is (5, 4)The code is:1shape(patients)The output is (4, 5).The code is:1shape(patients)The output is 5.8.Question 8The following code specifies a DataFrame that captures information about patients. What is the code for getting the mean of the age column, and what is the output?Note that you can try this out in the Jupyter Notebook for "Python Basics Part 2".1 pointThe code is:1mean(age)The output is 46.8.The code is:1mean(patients.age)The output is 47.9.The code is:1data['age'].meanThe output is 49.7.The code is:1patients['age'].mean()The output is 48.6.9.Question 9What are the areas of convergence that Professor Andrew Morris lists for personalised therapy? 1 pointBiology, medicine, healthcare, with datascience. Mathematics, computing, bioinformatics, withgenetics. Informatics, analytics, genomics, withphenotyping. Statistics, data mining, data visualisation, withgenotyping. 10.Question 10Whichof the following statements below is incorrect? 1 pointIHDP’svision is to join up disparate data sets and turn such data into intelligenceto improve cancer outcomes. Datascience methods used to join up cancer data cannot be applied to other clinicalareas. IHDP aims to harness the power of informatics todeliver value to patients, healthcare professionals and the wider NHS. TheScottish Cancer Registry and Intelligence Service plan to apply more analyticalfunctions to the data being held within the registry.

Step 6: AI in Medicine Artificial Intelligence (AI) is indeed revolutionizing healthcare. For instance, AI is used in predictive analytics to identify trends and make predictions about disease outbreaks. This is done by analyzing vast amounts of data from various sources such as hospitals, health records, and even social media. An example of this is Google's DeepMind Health project, which uses AI to mine medical records in order to provide better and faster health services. Moreover, precision medicine uses AI to tailor treatment to individual patients based on their genetic makeup. This means that instead of a one-size-fits-all approach, treatments are customized for each patient, increasing the chances of success. For example, IBM Watson Genomics uses AI to analyze a patient's genetic data and provide personalized treatment options. Robotic surgery, powered by AI, allows for more precise and minimally invasive procedures. The da Vinci Surgical System, for instance, uses AI to assist surgeons in performing complex surgeries with greater precision and control than conventional techniques. Step 7: Advantages of AI AI offers numerous advantages. It can process vast amounts of data quickly and accurately, making it invaluable in fields like finance and healthcare. For example, AI algorithms can analyze financial markets and make predictions with a level of speed and accuracy that surpasses human capabilities. AI can also perform tasks 24/7 without fatigue, making it more reliable than human workers in certain contexts. For instance, AI-powered customer service bots can handle customer inquiries round the clock, providing businesses with a cost-effective way to improve customer service. Step 8: Ethical Considerations in AI However, AI also raises ethical concerns. Bias in algorithms can lead to unfair outcomes. For example, if an AI system is trained on data that reflects societal biases, it may perpetuate or even amplify these biases. Data privacy is another concern, as AI's ability to analyze and store vast amounts of personal data could potentially be misused. For instance, there have been concerns about how tech companies use AI to analyze user data for targeted advertising. The impact of AI on employment is also a concern, as AI could potentially replace human workers in certain fields. For example, self-driving vehicles could potentially replace truck drivers. Step 9: Future Trends in AI Looking ahead, AI is set to continue evolving. Explainable AI, which aims to make AI decisions more transparent and understandable, is an emerging field. This is important as it can help build trust in AI systems and ensure they are used responsibly. The integration of AI with other technologies like the Internet of Things (IoT) and blockchain also holds promise. For instance, AI could be used to analyze data from IoT devices to make smarter decisions, while blockchain could provide a secure and transparent way to track AI decisions. (write reference

A personalized approach to healthcare that tailors medical treatment to individual characteristics is known as __________ *Personal TreatmentGenetic TreatmentPrecision TreatmentNone of the above

Health informatics merges information technology with health sciences to improve healthcare delivery, enhance patient outcomes, and manage health information:Question 1Answera.Trueb.FalseClear my choice

2.Question 2Which of the following statements is true? 1 pointMedical data is estimated to double in volume every 2-3 months on averageMost hospitals use a standardized IT and electronic health record workflowMedical data is generated in an organized systematic way that is very amenable to data science techniques and applicationsClinical structured data is not well suited for traditional programming approaches compared to imaging data

"Many experts believe that artificial intelligence (AI) will play a significant role in the future of healthcare. AI systems can analyze vast amounts of medical data quickly, leading to faster diagnoses and more personalized treatment options." What is the evidence or reasoning provided to support the conclusion?The current absence of AI systemsThe availability of medical dataFaster diagnoses and more personalized treatment optionsThe lack of expertise among healthcare professionals