👩‍⚖️Victory for 22 women who didn’t know their videos would be posted on porn site: A US judge has awarded $13m in damages to 22 women who were defrauded by the owners of GirlsDoPorn, a website specialising in “amateur”-style pornography. The women were coerced and tricked into making pornography that was released on to some of the biggest adult sites in the world without their consent, leaving some of them suicidal. The San Diego superior court heard evidence from the women, Jane Does 1 to 22, in a case their lawyers say has “exposed the rotten underbelly of the San Diego sex industry.” Full Story 

🏳️‍🌈Pakistan to provide free healthcare for trans people: Pakistan has extended a government health insurance scheme to transgender people for the first time, in a move aimed at ending discrimination in access to care, an official said. All transgender people are now eligible for medical treatment including reconstructive surgery under the scheme, which was set up to enable poor and marginalised communities in Pakistan to access healthcare. Prime Minister Imran Khan said his government was "taking responsibility" for trans people, who say they are routinely denied treatment and can face harassment or ridicule from hospital staff and patients. "It is part of a grand programme to provide health insurance not just to the poor but the vulnerable sections of society, including ... transgender (people)," said Zafar Mirza, a special assistant to Khan. Full Story

👾Artificial intelligence beats doctors in detecting breast cancer, new research shows: While there has been controversy over when and how often women should be screened for breast cancer using mammograms, studies consistently show that screening can lead to earlier detection of the disease, when it’s more treatable. So improving how effectively mammograms can detect abnormal growths that could be cancerous is a priority in the field. Artificial Intelligence could play a role in accomplishing that—computer-based machine learning might help doctors to read mammograms more accurately. In a study published Jan. 1 in Nature (the world's leading multidisciplinary science journal), researchers from Google Health, and from universities in the U.S. and U.K., report on an AI model that reads mammograms with fewer false positives and false negatives than human experts. The algorithm, based on mammograms taken from more than 76,000 women in the U.K. and more than 15,000 in the U.S., reduced false positive rates by nearly 6% in the U.S., where women are screened every one to two years, and by 1.2% in the U.K., where women are screened every three years. The AI model also lowered false negatives by more than 9% in the U.S. and by nearly 3% in the U.K. Full Story 
 

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