St. George’s University, Grenada, West Indies: Five Pioneering Applications of AI in Medicine
- Written by St. George's University School of Medicine
1. Diagnostic Assistance AI systems analyze X-rays and MRI scans to diagnose cancer, retinal diseases, and pneumonia. In cardiology, deep learning algorithms diagnose heart attacks like cardiologists. AI networks trained with clinical images assist in dermatological diagnoses, accurately classifying skin lesions. Studies show AI can match or exceed human experts' diagnostic accuracy and speed.
2. Robot-Assisted Surgery AI enhances surgical decision-making by integrating information from various data sources, including surgical guidelines and research insights. AI-equipped surgical robots assist surgeons with greater precision during procedures, offering minimally invasive options that result in shorter hospital stays, quicker recovery, and reduced patient pain.
3. Medical Education and Training Medical schools are integrating AI tools into their Doctor of Medicine programs:
- Learner-oriented AI: Tools that help students receive and understand new information.
- Instructor-oriented AI: Tools that reduce instructors' workload, provide insights about students, and incorporate innovations into classrooms.
- Institution-oriented AI: Tools that inform decisions about managing and administering schools and programs.
4. Natural Language Processing (NLP) for Health Care Records AI-driven NLP systems analyze and extract valuable information from unstructured medical records, improving coding, billing, and data management efficiency. These systems convert textual data into structured, usable information, automate billing and coding processes, and provide critical data points to practitioners, flagging potential issues and suggesting treatment options.
5. Genomics AI revolutionizes genomics by enhancing biological data analysis, interpretation, and application. AI sequences genomes faster and more accurately than humans, identifying patterns and mutations in DNA. Machine learning algorithms predict disease risks based on genetic makeup and individuals' responses to drugs or therapies, enabling personalized treatment plans.
Dr. Anna Cyrus-Murden, Assistant Dean of Simulation, Department of Clinical Skills at SGU, stated, "AI in medicine empowers healthcare professionals with advanced tools, not replacements, improving their work amidst a physician shortage. By harnessing data-driven insights and capabilities, AI has the potential to enhance outcomes, reduce disparities in treatment, and develop more efficient, patient-centered care. From redefining how diseases are diagnosed to pioneering tailored treatments and empowering patients with information, the journey of AI in medicine is ever-evolving as new capabilities are continually realized."
SGU remains committed to advancing medical education and innovation. To know more about SGU, click here[5].
Hashtag: #StGeorge
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References
- ^ Media OutReach Newswire (www.media-outreach.com)
- ^ poised to become a medical AI (www.biospectrumasia.com)
- ^ powerhouse (www.biospectrumasia.com)
- ^ substantial investments (www.insights10.com)
- ^ here (www.sgu.edu)
Authors: St. George's University School of Medicine
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