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AI in Medicine

The University of Chicago_052921C
[The University of Chicago]


- Overview

AI in medicine is a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care. 

AI scans data and uses statistical methods, probability theory, and machine and deep learning to find patterns that are difficult for the human mind to see. One of the most fertile grounds to take advantage of AI in medicine is the acquisition and interpretation of images for diagnosis - such as ultrasound, computerized tomography (CT) or magnetic resonance imaging (MRI). 

The results, in the form of digital images, must be interpreted by the doctors, who with their training and expertise can extract useful information to reach a diagnosis. As the number of images that are acquired - and their quality, sensitivity and resolution - increase steadily, researchers are working to develop technologies to help radiologists assess these images more quickly, accurately and effectively. 

This high-level computing augments physicians' knowledge to help doctors make predictions and treatment recommendations that are personalized for individual patients. 


- AI in Healthcare

Artificial intelligence (AI) is used in many ways in medicine, including: 

  • Diagnosing patients
  • Drug discovery and development
  • Improving communication between doctors and patients
  • Transcribing medical documents, such as prescriptions
  • Remotely treating patients
  • Detecting diseases faster
  • Providing personalized treatment plans
  • Automating certain processes, such as drug discovery or diagnostics
  • Reducing human error
  • Providing patient services 24/7
  • Reading medical images, X-rays, and scans
  • Analyzing discussions with patients
  • Entering required information directly into EHR systems

AI can make healthcare more accurate, accessible, and sustainable. AI algorithms can rapidly analyze health data, leading to precise diagnoses and timely interventions. Predictive models powered by AI can detect patterns and trends, aiding disease prevention and personalized treatment plans. 

However, AI-based systems raise concerns regarding data security and privacy. Because health records are important and vulnerable, hackers often target them during data breaches.


- AI in Pancreatic Cancer

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of only 11%. The median overall survival for pancreatic cancer patients diagnosed with early screening was nearly 10 years, compared with 1.5 years for patients with pancreatic cancer not diagnosed with early screening. 

Therefore, the early diagnosis and early treatment of pancreatic cancer is particularly critical. However, as a rare disease of pancreatic cancer, the general screening cost is high, the existing tumor markers are not accurate enough, and the therapeutic effect is not exact. 

In terms of early diagnosis, artificial intelligence (AI) technology can quickly locate high-risk groups through medical imaging, pathological examinations, biomarkers, etc., and screen pancreatic cancer lesions at an early stage. At the same time, AI algorithms can also be used to predict survival time, recurrence risk, metastasis, and treatment response that may affect prognosis. In addition, artificial intelligence is widely used in pancreatic cancer health records, estimation of medical imaging



[More to come ...]

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