TOPIC 1- What will be the problem you plan to solve with AI? (TP070151)

 






  The problem that I plan to solve with AI is about healthcare, which is predictive analysis for patient care. The application of AI in healthcare industry is to fully utilize the huge amount of data generated in the healthcare settings ranging from patient medical histories, diagnostic tests, treatment records, to wearable health devices data. By doing so, it could analyze the data to predict any possible health conditions before it get worsen. 

  Now I'm going to explain how it works. First of all, let's start off with the data integration and analysis. AI system combine a wide range of data including electronic health records (EHRs), genetic information, imaging data and comments from healthcare professionals all around the world. The algorithms can detect patterns and connections that are hard for humans to notice immediately.

  Up next is predictive modelling. By combining all the data, AI creates a predictive models that could predict possible healthcare risks. For instance, it could predict whether a patient would develop chronic diseases based on their medical history, lifestyle and genetic information such as diabetes, heart diseases or any certain forms of cancer.

  With the help of AI, healthcare providers can design a preventative treatments or plan for patient to reduce the risk of their possible chronic diseases. For example, the plan could include a diet and exercise plan for diabetes patient or start the treatment earlier for patient with potential heart diseases.

  Not only that, predictive analysis could also help to develop a more precise treatment strategies by evaluate patient's profile such as their genetic information to ensure them to get the best medicine that are effective for them with a lower side effects.

  In conclusion, by using the help of AI, it could improve patient outcomes, reduce the cost and improve efficiency. By discovering those problems earlier, patient could get a better treatment and it can enhance the quality of their life. It could also reduce the cost by avoiding expensive emergency treatments or surgery for severe diseases. Lastly it could improve the efficiency by allocating and prioritize resources to patient who need it the most.


REFERENCES:
1. Philips. (2022, November 15). Predictive analytics in healthcare: three real-world examples. https://www.philips.com/a-w/about/news/archive/features/20200604-predictive-analytics-in-healthcare-three-real-world-examples.html

2. Badawy, M., Ramadan, N., & Hefny, H. A. (2023). Healthcare predictive analytics using machine learning and deep learning techniques: a survey. Journal of Electrical Systems and Information Technology, 10(1). https://doi.org/10.1186/s43067-023-00108-y

2.EDIEDITED BY: PATRICK WOO SOON TAT (TP070151)

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