생명공학과 의학분야에서의 인공지능의 활용

소개글

생명공학과 의학분야에서의 인공지능의 활용에 대한 보고서 자료입니다.

목차

1. AI를 이용한 질병 진단(Diagnose diseases with AI)
2. 신속한 신약 개발(Develop drugs faster)
3. 개인 맞춤 치료(Personalize treatment)
4. 유전자 편집 개선(Improve gene editing)
5. 배우고 느낀 점(Learn and impression points)
6. 참고자료(Reference)

본문내용

AI for Diagnostics, Drug Development, Treatment Personalization and Gene Editing
by
Markus Schmitt

Machine Learning has made great advances in pharma and biotech efficiency. This post summarizes the top 4 applications of AI in medicine today:
1. Diagnose diseases
Correctly diagnosing diseases takes years of medical training. Even then, diagnostics is often an arduous, time-consuming process. In many fields, the demand for experts far exceeds the available supply. This puts doctors under strain and often delays life-saving patient diagnostics.
Machine Learning – particularly Deep Learning algorithms – have recently made huge advances in automatically diagnosing diseases, making diagnostics cheaper and more accessible.
How machines learn to diagnose
Machine Learning algorithms can learn to see patterns similarly to the way doctors see them. A key difference is that algorithms need a lot of concrete examples – many thousands – in order to learn. And these examples need to be neatly digitized – machines can’t read between the lines in textbooks.
So Machine Learning is particularly helpful in areas where the diagnostic information a doctor examines is already digitized.
Such as:
• Detecting lung cancer or strokes based on CT scans
• Assessing the risk of sudden cardiac death or other heart diseases based on electrocardiograms and cardiac MRI images
• Classifying skin lesions in skin images
• Finding indicators of diabetic retinopathy in eye images

키워드

인공지능,   의생명공학,   개인 맞춤치료,   유전자 편집