Wednesday December 11, 2019

China Excludes Taiwan from Participation in World Health Assembly

WHO estimates it needs $98 million to run its Ebola operation. It is facing a funding shortfall of some $63 million

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World health assembly
Director General of the World Health Organization (WHO) Tedros Adhanom Ghebreyesus attends the 72nd World Health Assembly in Geneva, Switzerland, May 20, 2019. VOA

Taiwan is protesting China’s decision to exclude the island from participation in the annual World Health Assembly, calling such action an unjustified political move that could harm global health.

The 72nd session of the World Health Organization’s World Health Assembly takes place May 20-28 in Geneva, Switzerland.

This move is particularly ironic this year, as the theme of the assembly is universal health coverage. Taiwan’s national health system is widely considered one of the best in the world.Taiwan’s minister of health and welfare, Chen Shih-chung, says the island is ready to share its experiences on how to achieve affordable, efficient universal health coverage with the global community.

world health assembly
FILE – Chen Shih-chung, Taiwan’s minister of Health and Welfare, is interviewed by Reuters ahead of the World Health Assembly of the World Health Organization in Geneva, May 20, 2017. VOA

“However, under pressure from the People’s Republic of China, Taiwan is currently excluded by WHO from the global health network,” Chen said. “Inviting Taiwan to participate in the WHA would be consistent with WHO’s espousal of health for all.”

The health minister notes Taiwan’s exclusion poses health risks to everyone. Chen says diseases do not stop at borders, and international cooperation is needed to combat epidemics that could spread to every corner of the world.

Chen tells VOA he has written several letters to WHO chief Tedros Adhanom Ghebreyesus to protest Taiwan’s exclusion from the World Health Assembly. Chen says he has received no response. He says WHO has even rejected Taiwan’s offer for help in combating the Ebola epidemic in eastern Democratic Republic of Congo.

world health assembly
WHO estimates it needs $98 million to run its Ebola operation. It is facing a funding shortfall of some $63 million. Wikimedia Commons

“Our president announced we would donate $1 million U.S. to combat Ebola; but this donation, even this donation was not accepted by the WHO. So, this is a pity in our situation. We want to do something, but WHO did not accept us to do something for the world,” Chen said.

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WHO estimates it needs $98 million to run its Ebola operation. It is facing a funding shortfall of some $63 million.

Despite pressure from China, Taiwan’s officials say they have received support for their bid to join the WHO from a number of countries including the United States, Japan, Germany and Australia. (VOA)

Next Story

AI Can Better Help Doctors to Identify Cancer Cells in Human Body

The process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone

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Cancer
The AI algorithm helps pathologists obtain the most accurate Cancer cell analysis - in a much faster way. Pixabay

Researchers at University of Texas Southwestern have developed a software tool that uses Artificial Intelligence (AI) to recognize Cancer cells from digital pathology images – giving clinicians a powerful way of predicting patient outcomes.

The spatial distribution of different types of cells can reveal a cancer’s growth pattern, its relationship with the surrounding microenvironment, and the body’s immune response.

But the process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone.

“To make a diagnosis, pathologists usually only examine several ‘representative’ regions in detail, rather than the whole slide. However, some important details could be missed by this approach,” said Dr. Guanghua “Andy” Xiao, corresponding author of a study published in EbioMedicine.

A major technical challenge in systematically studying the tumor microenvironment is how to automatically classify different types of cells and quantify their spatial distributions.

The AI algorithm that Dr Xiao and his team developed, called “ConvPath”, overcomes these obstacles by using AI to classify cell types from lung cancer pathology images.

Cancer
Researchers at University of Texas Southwestern have developed a software tool that uses Artificial Intelligence (AI) to recognize Cancer Cells from digital pathology images – giving clinicians a powerful way of predicting patient outcomes. Pixabay

The ConvPath algorithm can “look” at cells and identify their types based on their appearance in the pathology images using an AI algorithm that learns from human pathologists.

The algorithm helps pathologists obtain the most accurate cancer cell analysis – in a much faster way.

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“It is time-consuming and difficult for pathologists to locate very small tumour regions in tissue images, so this could greatly reduce the time that pathologists need to spend on each image,” said Dr Xiao. (IANS)