Event topics

[Experience Economy] Faster, more accurate diagnoses: Applications of AI
Kind: Event topics  Organization: Department of International Cooperation  Publish Date: 2020-10-28 15:13
Open new window for Taiwan established an artificial intelligence school, Taiwan AI Academy, in 2018.(png)
"Hey, Siri, how is the weather today?"
"Okay, Google, call mom!"

When Google DeepMind's Alpha Go shockingly defeated legendary Go player Lee Se-dol, the terms artificial intelligence (AI), machine learning and deep learning were propelled into the technological mainstream.
AI is generally defined as the capacity for a computer or machine to exhibit or simulate intelligent behavior such as Tesla's self-driving car and Apple's digital assistant Siri. It is a thriving field and the focus of much research and investment.
Machine learning is the ability of an AI system to extract information from raw data and learn to make predictions from new data.
Deep learning combines artificial intelligence with machine learning. It is concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning has received much attention lately both in the consumer world and throughout the medical community.
When it comes to health care, although using AI or machine learning to make diagnoses is new, there has been exciting and promising progress.

Extracting blood vessels in the eye
Detecting abnormal blood vessels is useful for diagnosing diabetes and heart disease. Some patients with diabetes will have retinopathy, but retinopathy is difficult to detect early.
Nowadays, analysis techniques for diabetic retinopathy have been developed, and only the original retinal images can be read to interpret the retinal blood vessels. Interpreting the image by AI can clearly mark the location of the symptoms, effectively assisting the physician to make an accurate diagnosis.

Detecting lung cancer
Computer tomography (CT) is widely used for lung cancer diagnosis. However, because visual representations of benign (non-cancerous) and malignant (cancerous) lesions in CT scans are similar, a CT scan cannot always provide a reliable diagnosis. This is true even for a thoracic radiologist with many years of experience.
The rapid growth of CT scan analysis has generated a pressing need for advanced computational tools to assist radiologists with the screening progress.
To improve radiologists' diagnostic performance, the scientists have proposed a deep learning solution. Based on research findings, using a deep learning-based solution improves diagnostic performance overall, and radiologists with less experience benefit from the system the most.

Limitations and challenges
Although great promise has been shown with deep learning algorithms in a variety of tasks across radiology and medicine, these systems are far from perfect.
In the complex world of healthcare, AI tools can support human practitioners to provide faster service and more accurate diagnoses, and analyze data to identify trends or genetic information that may predispose someone to a particular disease.
When saving minutes can mean saving lives, AI and machine learning may be transformative for healthcare workers and patients.

International exchange
In order to promote the development of domestic industries and cultivate professionals in the field of AI technology, Taiwan established an artificial intelligence school, Taiwan AI Academy, in 2018. Over the past few years, it has gradually become well-known internationally. Not only the governments of Germany, Japan, Thailand, Malaysia and other countries came to visit the Taiwan AI Academy and express their willingness to cooperate, but also many foreign companies contacted, hoping to send employees to Taiwan and study in artificial intelligence schools.

Update: 2020-04-17
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